Tag: Management

  • [Solved] Week 8 Discussion- Managing People and Promoting Collab

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    **A Reflection on Developing Individuals and Teams** In this Discussion, you will reflect on your personal experiences and what you have learned so far in this course about working with members of a team. Every member of a team brings valuable experience, knowledge, and skills with them. They also b…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    **A Reflection on Developing Individuals and Teams**
    In this Discussion, you will reflect on your personal experiences and what you have learned so far in this course about working with members of a team. Every member of a team brings valuable experience, knowledge, and skills with them. They also bring personal behaviors, beliefs, and challenges. Being able to mitigate conflicts and navigate individual characteristics requires a knowledgeable and skillful manager that monitors team function and employs necessary management strategies in a timely and effective manner.
    **To prepare for this Discussion:**
    · Consider what you have learned in this course and through your own professional experience related to developing individuals and teams.
    \
    Week5LearningResources-ManagingPeopleandPromotingCollab.docx](https://www.sweetstudy.com/files/week5learningresources-managingpeopleandpromotingcollab-docx-10347927 "Week5LearningResources-ManagingPeopleandPromotingCollab.docx")
    \
    Week6LearningResources-ManagingPeoplePromotingCollab.docx](https://www.sweetstudy.com/files/week6learningresources-managingpeoplepromotingcollab-docx-10347929 "Week6LearningResources-ManagingPeoplePromotingCollab.docx")
    \
    Week7LearningResources-ManagingPeople0PromotingCollab.docx](https://www.sweetstudy.com/files/week7learningresources-managingpeople0promotingcollab-docx-10347933 "Week7LearningResources-ManagingPeople0PromotingCollab.docx")

  • [Solved] ECO IV J

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    – ## EconomicsforManagersECO6301UnitIVJournal.docx – ## UnitIVStudyGuide.pdf – ## UnitIIIStudyGuide.pdf **## EconomicsforManagersECO6301UnitIVJournal.docx** 2 Economics for Managers ECO 6301 **Unit IV Journal** This journal measures your mastery of ULOs 1.3, 3.1, 5.1, and 6.3. **Journal objective:**…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    – ## EconomicsforManagersECO6301UnitIVJournal.docx

    – ## UnitIVStudyGuide.pdf

    – ## UnitIIIStudyGuide.pdf

    **## EconomicsforManagersECO6301UnitIVJournal.docx**

    2

    Economics for Managers ECO 6301

    **Unit IV Journal**

    This journal measures your mastery of ULOs 1.3, 3.1, 5.1, and 6.3.

    **Journal objective:** International trade can have significant effects on domestic markets. For use in the assignment, identify a good that the United States imports and a good the United States exports.

    **Length:** Your submission is required to be at least 2-pages and not more than 5 pages in length, not including the title page and references.

    **References:** A minimum of 3 peer-reviewed references are required, any additional resources used are required to be scholarly/academic in nature and found in the CSU Library. APA formatting is required to be used for citations and references. Use this definition to define the term in the instructions.

    **Definitions:** Scholarly journals are sometimes called academic journals. The terms are often used interchangeably to describe the same type of publication. These types of publications are published by universities, academic institutions, professional associations, and commercial enterprises and are compiled by scholars, academics, and other subject authorities.

    **Details:** In your paper, include the following:

    · Introduction

    · supply or demand for the particular good,

    · the competitiveness of that good’s market, and

    · how the change in competitiveness affects market structure as well as equilibrium price and quantity.

    · Stepping away from the import/export examples, describe how opening up to trade specifically affects a domestic monopoly. Include an explanation, using game theory, of how even a single additional competitor can lead to a market outcome similar to perfect competition.

    · Conclusion

    **## UnitIVStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit IV

    At the end of this unit, you should be able to:

    5. Apply game theory to pricing and to output decisions in an oligopoly market.
    5.1 Explain how game theory can lead to fierce competition even with only a few competitors in a

    market.

    6. Analyze the basis of trade.
    6.3 Describe how countries opening to international trade affect the market structure of domestic

    industries.

    Required Unit Resources

    Chapter 11: Foreign Exchange, Trade, and Bubbles (ULO 6.3)

    Chapter 15: Strategic Games (ULO 5.1)

    Chapter 16: Bargaining (ULO 5.1)

    Unit Lesson

    Lesson: International Trade and Strategic Behavior (ULOs 5.1, 6.3)
    This lesson will introduce you to the topics of international trade and strategic behavior that are the focus of
    this unit.

    Trade goes back to the dawn of civilization. As travel has become easier and more accessible, international
    trade has connected regions from across the globe. Unit I introduced the benefits of trade with the Starburst
    example. The same benefits hold when the exchange crosses international borders.

    In the Starburst example, the benefits of trade arose from differences in flavor preferences. Generally
    speaking, the benefits of trade arise from differences in opportunity costs. The opportunity costs are not about
    what we give up when we consume, but what we give up when we produce. That is, there are differences in
    production capabilities between people, regions, and countries. Iowa and Nebraska, for example are well
    equipped for producing corn. Colombia is well equipped for producing coffee. Countries with large populations
    and limited capital are well equipped for producing labor intensive goods. Countries with smaller populations
    but more capital are well equipped for producing capital intensive goods.

    If a Country Can Be Self-Sufficient, Should it Be?

    Even if a country can produce everything it needs, it is still better off trading due to differences in opportunity
    costs. Opportunity costs are the value of what you give up when making a choice. The United States might be
    able to produce bananas, but the resources required to produce enough bananas for the entire population
    could be used to produce other things. Producing enough bananas would take more land. Producing enough
    bananas would likely take more buildings and energy to create the proper tropical climate to grow bananas.
    This would all take resources away from producing corn or cars. The labor required to grow more bananas
    would also take labor away from software development or education. Growing bananas in the United States
    would mean giving up a lot of corn (or cars or software development or education), but producing corn (or
    cars or software or education) would not result in losing much banana production.

    UNIT IV STUDY GUIDE
    International Trade and Strategic Behavior

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Having a lower opportunity cost to produce a certain good is called having a comparative advantage in that
    good. Basing production on comparative advantage leads to more overall production that can then be traded
    for other goods. In addition to benefiting from a lower opportunity cost, focusing production on specific goods
    also allows for specialization so producers get even better at producing their goods. By specializing, people
    get better at their tasks and also have time to develop new and better ways of producing. If people are trying
    to produce multiple things, they cannot put the same level of attention into improving specific processes. You
    might be familiar with the phrase “a jack of all trades, but a master of none.” That is what happens without
    specialization.

    Despite the benefits of trade, fear of international trade is common. There are concerns that jobs are lost to
    foreign competition. Certainly, there are specific jobs that will no longer be needed domestically. If the United
    States, for example, had been self-sufficiently producing bananas and then opened up to international trade
    and started importing bananas, jobs in the banana production market would no longer be needed. That does
    not mean, however, that overall jobs are lost to international trade. Jobs are gained from the ability to export
    goods. Jobs are also gained because the resources that were previously used to grow bananas can now be
    used to produce other goods. Also, the lower prices for bananas enable consumers to redirect their spending
    to other goods.

    Trade Protection

    What you might have picked up from the example of the bananas is that despite the benefits of trade, banana
    producers would still have a strong incentive to prevent competition from foreign banana producers. Banana
    producers then have an incentive to lobby the government for protection from foreign competition. This
    protection usually comes in the form of tariffs (there are other forms of trade protection, such as quotas, but
    tariffs are by far the most common).

    Tariffs are in the news a lot, particularly between China and the United States in 2019. Basic economic theory
    tells us that tariffs are simply passed on to consumers. This is not, however, what we necessarily see in
    practice. Elasticity is an important determinant in tax incidence (that is, who bears the burden of a tax). Tax
    incidence is determined by the relative elasticities between supply and demand. From a trade perspective,
    exchange rates can serve as a way for countries to absorb the tariff without having to raise their prices. China
    lets their currency depreciate to keep the prices of their products the same. When this happens, anybody
    holding Chinese currency essentially pays the tariff. Of course, that does not mean there are not costs to the
    United States from assessing tariffs. When China devalues their currency, U.S. produced goods become
    more expensive in China, so quantity demanded for U.S. exports goes down. Ultimately, both countries bear
    some of the burden from tariffs.

    So why assess tariffs? The most obvious reason is as described above: to help domestic interest groups.
    There can be other reasons, however, and to see that, we have to introduce some game theory.

    Game Theory

    Game theory is applied to decision-making where one party’s actions affect another party’s outcome. Game
    theory is not applicable to perfectly competitive markets because individual producers cannot affect the
    market outcome. Game theory is not applicable to monopoly because there is only one producer in a
    monopoly. Game theory is applicable to oligopolies where there are a handful of producers; so what one
    producer does affects the other producers.

    If Coke, for example, comes out with a new product, that new product will likely affect Pepsi and Dr Pepper.
    If Coke changes their price or embarks on a new marketing campaign, Pepsi and Dr Pepper will likely be
    affected. Pepsi and Dr Pepper, thus, need to decide how they will respond to Coke’s actions. Coke will also
    need to anticipate Pepsi and Dr Pepper’s response when deciding the action they take (you can think of it
    like the Battle of Wits from The Princess Bride). The optimal strategy for a “game” is determined by
    evaluating likely strategies by opponents and expected outcomes. Optimal strategies can also be affected
    by the structure of a game. Some games are sequential, where one player makes a decision and then the
    other player makes a decision in response to the first player’s decision. Other games are simultaneous
    where players make their decision at the same time. Ultimately, the outcome of a game is driven by the
    likely outcomes.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Game theory can also be applied to bargaining situations, for example, when bargaining over trade
    agreements. Trade agreements are often termed “free trade agreements,” but that is a bit of a misnomer.
    Certainly, most trade agreements eliminate tariffs, but if that is all that was involved, the agreement could be
    written on a cocktail napkin. Instead, trade agreements often include restrictions or allowances for subsidies,
    requirement wages, environmental rules, and rules of origin (rules of origin are requirements on the countries
    where intermediate goods in the production process were produced). All of these requirements can move the
    agreement away from free trade.

    This is where game theory and bargaining can play a role. Consider trade between the United States and
    China. China places considerable trade restrictions on imports from the United States, and the United States
    has historically not put many on imports from China. Now, per trade theory, this is still beneficial to the United
    States. That is, the United States still benefits from getting goods produced at a lower cost than companies in
    the United States could produce them. The United States would benefit even more, however, if China did not
    have trade restrictions. China, however, feels they benefit from their trade restrictions (standard economic
    theory would say they do not).

    So how does the United States get China to reduce their trade restrictions?

    One possible approach is to employ trade restrictions against Chinese products. This can be thought of as a
    game of chicken, except where the costs are steeper for China than for the United States. The risk, of course,
    for the United States, is that the costs are actually steeper for the United States.

    There are other factors that can matter for a negotiation as well. You might be familiar with the phrase,
    “Whoever gives a number first, loses.” That would suggest that being a first mover could put a bargainer at a
    disadvantage. This is because moving first reveals information to your opponent that they can use to decide
    the action. Credibility to commit to a position matters too. In a repeated game, if one party cannot credibly
    stick to their position through multiple iterations of a game, then the other party can benefit by simply waiting
    out the other party. In the case of the United States and China, the frequency of elections can be a handicap.
    The Chinese government will likely be in power for the foreseeable future, while any given United States
    administration only has certainty of four years at a time to be in power. Fortunately, you can see a lot of these
    concepts play out in the real world by paying attention to the news.

    **## UnitIIIStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit III

    At the end of this unit, you should be able to:

    1. Evaluate the ethical outcomes of free market outcomes using supply and demand models.
    1.3 Compare and contrast the effect perfect competition and monopoly have on total welfare.

    3. Analyze how price and output influence profit maximization under different market structures.

    3.1 Compare and contrast the market outcomes for perfect competition, monopoly, oligopoly, and
    monopolistic competition.

    Required Unit Resources

    Chapter 8: Understanding Markets and Industry Changes (ULO 3.1)

    Chapter 9: Market Structure and Long-Run Equilibrium (ULO 3.1)

    Chapter 10: Strategy: The Quest to Keep Profit from Eroding (ULO 1.3)

    Article: Price Caps, Oligopoly, and Entry (ULO 3.1)

    Unit Lesson

    Unit Material (ULO 2.1)
    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    Supply and Demand

    In a market, supply and demand come together to determine the equilibrium price and quantity. When demand
    increases, price and quantity increase. When supply increases price decreases and quantity increases.

    UNIT III STUDY GUIDE
    Market Structures and Profit

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Demand

    There are several factors that can cause demand to change. Economists group these reasons into five
    main factors:

    Businesses need to know not just these factors but how these factors affect the industry of their business.

    Changes in income, for example, do not affect all businesses the same. Economists categorize goods as
    normal goods, which are goods whose demand increases as income increases, and inferior goods, which are
    goods whose demand increases as income decreases. An example of a normal good would be eating out.
    The more income a person has, the more likely they are to eat at restaurants rather than prepare meals at
    home. Candy, possibly surprisingly, is an inferior good. When people experience lower incomes, they cannot
    afford as much entertainment as before, so candy offers an inexpensive pleasure.

    Changes in the price of related goods is another factor that can have different effects based on specific
    circumstances. Some goods are related in consumption. These are called complements. Peanut butter and
    jelly are an example of complements. If the price of a complement decreases (say, peanut butter), then the
    demand for the good in question (say, jelly) will go up. After all, if you are buying more peanut butter, you are
    going to need more jelly to go with it. Substitutes are goods that compete in consumption. Coke and Dr
    Pepper, for example, are substitutes. If the price of Coke goes down, consumers are more likely to buy Coke,
    and, thus, less likely to buy Dr Pepper. So if the price of a substitute good decreases, the demand for the
    good in question goes down.

    Most of the remaining factors work as might be expected. If the number of demands increases, demand for a
    particular good will increase. Imagine sitting in a waiting room as your oil gets changed. There is a vending
    machine there. You might be tempted to get something. If another person walks into the waiting room, they
    will also be tempted to get something. As more and more people enter the waiting room, the likelihood that
    somebody will purchase from the vending machine increases. Most likely, multiple people will make a
    purchase from the vending machine. In other words, demand will increase.

    Add in tastes and preferences. If a particular product becomes popular (perhaps because of positive press,
    perhaps the product is seasonal, perhaps the product has experienced a change in quality), then more people
    are likely to want the product. In other words, demand increases.

    Finally, look at expectations. Expectations might be a little confusing. The important thing to remember is that
    when looking at the effects of changes in demand, the time frame is immediate. That is, the expectation is for
    some time in the future, but the analysis is what happens to demand right now. So, if consumers expect
    prices to increase in the future, they will want to buy more before prices rise. That is, demand will increase.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Supply

    There are also factors that can affect supply (as opposed to demand). Most of these factors are pretty straight
    forward. As the price of inputs increase, costs to the producers go up, so naturally the supply will decrease.
    For example, if the price of oranges goes up, the supply of orange juice will decrease.

    If the price of a similarly produced product increases, then the supply of the good in question will decrease.
    For example, if looking at the supply of vanilla ice cream and the price of chocolate ice cream increases, then
    the supply of vanilla ice cream will decrease as the resources used to make vanilla ice cream will be shifted
    over to make more chocolate ice cream to take advantage of the higher price.

    As with demand, the number of suppliers matters to supply. The more suppliers there are, the more
    production there is. This is fairly simple and straightforward.

    Technology is also an important factor for supply. An improvement in technology that makes production
    easier and cheaper will lead to an increase in the supply. It is unlikely that a firm would actually adopt new
    technology unless it had the express purpose of making production easier or cheaper. For example, self-
    checkout kiosks at grocery stores or fast food restaurants are technology that make the production process
    (or service delivery process) cheaper for companies. They do require an upfront investment in technology, but
    the payoff is lower operating costs in the future.

    Finally, expectations are important for supply and the same caution that applied to expectations with demand
    apply here. Firms respond now to expectations about the future. Another important note is that while it can
    often be easy to think of supply as production, it is better defined as what producers bring to market. So, if
    producers expect a price decrease in the future, they will want to rush to market what they can to take
    advantage of the relatively higher price. That is, the expectation of a future price decrease will result in an
    increase in supply right now.

    To learn how to draw a supply and demand graph in Microsoft Word, view the video How to Graph in Word.
    You can access closed-captioning once you access the video.

    Market Structure

    As mentioned in the beginning of the lesson, underlying the supply curve is the market structure. Economists
    differentiate market structures (identified by name later in the course) based on three characteristics. Those
    three characteristics are:

    • the number of sellers in a market (The number of buyers matters too, but that does not change
    among these four market structures.);

    • the homogeneity of production (This means how different the production is from one producer to the
    next; another way to think about this is whether you can identify the producer based on the product.);
    and

    • the existence, or not, of barriers to entry (also phrased free entry and exit).

    At one extreme of the market structures is perfect competition. Perfect competition is characterized by:

    • lots of sellers,
    • selling identical products, and
    • no barriers to entry (free entry and exit).

    At the other extreme of market structures is monopoly. Monopoly is characterized by:

    • one producer—and only one (If it is even two producers, it is a different market structure.),
    • selling a product that is unique in the market such that there are no close substitutes, and
    • impossible for competitors to enter.

    As you can see from the characteristics, monopoly is the opposite of perfect competition. These differences
    lead to some important outcomes for the different markets.

    ECO 6301, Economics for Managers 4

    UNIT x STUDY GUIDE
    Title

    Since there are many producers producing exactly the same thing, perfectly competitive firms do not have
    any influence on the overall market. They are very much a “drop in the bucket” relative to the market.
    Perfectly competitive firms must accept whatever the market price is. Monopolies, on the other hand, are the
    only supplier in their market, so their decisions have a big influence on the market outcome. Monopolists
    cannot exactly set their price; they must be mindful of their consumers. When deciding what price to set,
    monopolists have to balance the revenue they would gain from raising their prices with the revenue they
    would lose by selling a lower quantity (and vice versa if they are considering a price decrease).

    Without barriers to entry, if a firm can make excessive profits (known as economic profit), then other firms will
    enter the market, taking some of that profit away. Monopolies are protected by barriers to entry, so if they can
    earn large economic profits, there will not be any competition to come along and take those profits away.

    Perfectly competitive markets are the most efficient. They must be. If a firm is not as efficient as possible, it
    will be run out of the market. Monopolies do not need to be efficient since they are protected by barriers to
    entry. Monopolists, just like every firm, want to maximize profits. Maximizing profit for a monopolist, however,
    means not producing as much as they could so that they can charge a higher price.

    In between these extremes are monopolistic competition and oligopoly. Monopolistic competition is a lot like
    perfect competition, except that rather than producing identical products, the firms produce slightly different
    products. The difference might be slight, and they might even be just perceived, but they matter, at least
    somewhat, to the consumer. Think about hair stylists and barbers, for example. Some people have certain
    people they like to cut their hair. Some people do not care but might still base their purchasing decision on
    proximity or availability. These differentiations introduce a slight amount of pricing power into the market. The
    differentiations also give rise to the need for firms to advertise what it is about their product that sets them
    apart from competitors. Differentiation can also be a feature of oligopolies.

    Oligopolies are a lot like monopolies except there are some firms, not one, in the market. Think of it this way,
    if you can name the firms that account for a strong majority of the market share off the top of your head, the
    industry is an oligopoly. Oil/Gas companies, airlines, and automobile companies are examples of oligopoly
    markets. The barriers to entry are high but not insurmountable. This feature leads to strategic behavior
    between the firms as the action of one firm affects the outcomes of other firms in the market. Strategic
    behavior will be an important topic explored in future units.

    Reference

    Reynolds, S. S., & Rietzke, D. (2018). Price caps, oligopoly, and entry. Economic Theory, 66(3), 707–745.

    https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc
    t=true&db=bsu&AN=132338488&site=ehost-live&scope=site

    **## UnitIIIStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit III

    At the end of this unit, you should be able to:

    1. Evaluate the ethical outcomes of free market outcomes using supply and demand models.
    1.3 Compare and contrast the effect perfect competition and monopoly have on total welfare.

    3. Analyze how price and output influence profit maximization under different market structures.

    3.1 Compare and contrast the market outcomes for perfect competition, monopoly, oligopoly, and
    monopolistic competition.

    Required Unit Resources

    Chapter 8: Understanding Markets and Industry Changes (ULO 3.1)

    Chapter 9: Market Structure and Long-Run Equilibrium (ULO 3.1)

    Chapter 10: Strategy: The Quest to Keep Profit from Eroding (ULO 1.3)

    Article: Price Caps, Oligopoly, and Entry (ULO 3.1)

    Unit Lesson

    Unit Material (ULO 2.1)
    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    Supply and Demand

    In a market, supply and demand come together to determine the equilibrium price and quantity. When demand
    increases, price and quantity increase. When supply increases price decreases and quantity increases.

    UNIT III STUDY GUIDE
    Market Structures and Profit

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Demand

    There are several factors that can cause demand to change. Economists group these reasons into five
    main factors:

    Businesses need to know not just these factors but how these factors affect the industry of their business.

    Changes in income, for example, do not affect all businesses the same. Economists categorize goods as
    normal goods, which are goods whose demand increases as income increases, and inferior goods, which are
    goods whose demand increases as income decreases. An example of a normal good would be eating out.
    The more income a person has, the more likely they are to eat at restaurants rather than prepare meals at
    home. Candy, possibly surprisingly, is an inferior good. When people experience lower incomes, they cannot
    afford as much entertainment as before, so candy offers an inexpensive pleasure.

    Changes in the price of related goods is another factor that can have different effects based on specific
    circumstances. Some goods are related in consumption. These are called complements. Peanut butter and
    jelly are an example of complements. If the price of a complement decreases (say, peanut butter), then the
    demand for the good in question (say, jelly) will go up. After all, if you are buying more peanut butter, you are
    going to need more jelly to go with it. Substitutes are goods that compete in consumption. Coke and Dr
    Pepper, for example, are substitutes. If the price of Coke goes down, consumers are more likely to buy Coke,
    and, thus, less likely to buy Dr Pepper. So if the price of a substitute good decreases, the demand for the
    good in question goes down.

    Most of the remaining factors work as might be expected. If the number of demands increases, demand for a
    particular good will increase. Imagine sitting in a waiting room as your oil gets changed. There is a vending
    machine there. You might be tempted to get something. If another person walks into the waiting room, they
    will also be tempted to get something. As more and more people enter the waiting room, the likelihood that
    somebody will purchase from the vending machine increases. Most likely, multiple people will make a
    purchase from the vending machine. In other words, demand will increase.

    Add in tastes and preferences. If a particular product becomes popular (perhaps because of positive press,
    perhaps the product is seasonal, perhaps the product has experienced a change in quality), then more people
    are likely to want the product. In other words, demand increases.

    Finally, look at expectations. Expectations might be a little confusing. The important thing to remember is that
    when looking at the effects of changes in demand, the time frame is immediate. That is, the expectation is for
    some time in the future, but the analysis is what happens to demand right now. So, if consumers expect
    prices to increase in the future, they will want to buy more before prices rise. That is, demand will increase.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Supply

    There are also factors that can affect supply (as opposed to demand). Most of these factors are pretty straight
    forward. As the price of inputs increase, costs to the producers go up, so naturally the supply will decrease.
    For example, if the price of oranges goes up, the supply of orange juice will decrease.

    If the price of a similarly produced product increases, then the supply of the good in question will decrease.
    For example, if looking at the supply of vanilla ice cream and the price of chocolate ice cream increases, then
    the supply of vanilla ice cream will decrease as the resources used to make vanilla ice cream will be shifted
    over to make more chocolate ice cream to take advantage of the higher price.

    As with demand, the number of suppliers matters to supply. The more suppliers there are, the more
    production there is. This is fairly simple and straightforward.

    Technology is also an important factor for supply. An improvement in technology that makes production
    easier and cheaper will lead to an increase in the supply. It is unlikely that a firm would actually adopt new
    technology unless it had the express purpose of making production easier or cheaper. For example, self-
    checkout kiosks at grocery stores or fast food restaurants are technology that make the production process
    (or service delivery process) cheaper for companies. They do require an upfront investment in technology, but
    the payoff is lower operating costs in the future.

    Finally, expectations are important for supply and the same caution that applied to expectations with demand
    apply here. Firms respond now to expectations about the future. Another important note is that while it can
    often be easy to think of supply as production, it is better defined as what producers bring to market. So, if
    producers expect a price decrease in the future, they will want to rush to market what they can to take
    advantage of the relatively higher price. That is, the expectation of a future price decrease will result in an
    increase in supply right now.

    To learn how to draw a supply and demand graph in Microsoft Word, view the video How to Graph in Word.
    You can access closed-captioning once you access the video.

    Market Structure

    As mentioned in the beginning of the lesson, underlying the supply curve is the market structure. Economists
    differentiate market structures (identified by name later in the course) based on three characteristics. Those
    three characteristics are:

    • the number of sellers in a market (The number of buyers matters too, but that does not change
    among these four market structures.);

    • the homogeneity of production (This means how different the production is from one producer to the
    next; another way to think about this is whether you can identify the producer based on the product.);
    and

    • the existence, or not, of barriers to entry (also phrased free entry and exit).

    At one extreme of the market structures is perfect competition. Perfect competition is characterized by:

    • lots of sellers,
    • selling identical products, and
    • no barriers to entry (free entry and exit).

    At the other extreme of market structures is monopoly. Monopoly is characterized by:

    • one producer—and only one (If it is even two producers, it is a different market structure.),
    • selling a product that is unique in the market such that there are no close substitutes, and
    • impossible for competitors to enter.

    As you can see from the characteristics, monopoly is the opposite of perfect competition. These differences
    lead to some important outcomes for the different markets.

    ECO 6301, Economics for Managers 4

    UNIT x STUDY GUIDE
    Title

    Since there are many producers producing exactly the same thing, perfectly competitive firms do not have
    any influence on the overall market. They are very much a “drop in the bucket” relative to the market.
    Perfectly competitive firms must accept whatever the market price is. Monopolies, on the other hand, are the
    only supplier in their market, so their decisions have a big influence on the market outcome. Monopolists
    cannot exactly set their price; they must be mindful of their consumers. When deciding what price to set,
    monopolists have to balance the revenue they would gain from raising their prices with the revenue they
    would lose by selling a lower quantity (and vice versa if they are considering a price decrease).

    Without barriers to entry, if a firm can make excessive profits (known as economic profit), then other firms will
    enter the market, taking some of that profit away. Monopolies are protected by barriers to entry, so if they can
    earn large economic profits, there will not be any competition to come along and take those profits away.

    Perfectly competitive markets are the most efficient. They must be. If a firm is not as efficient as possible, it
    will be run out of the market. Monopolies do not need to be efficient since they are protected by barriers to
    entry. Monopolists, just like every firm, want to maximize profits. Maximizing profit for a monopolist, however,
    means not producing as much as they could so that they can charge a higher price.

    In between these extremes are monopolistic competition and oligopoly. Monopolistic competition is a lot like
    perfect competition, except that rather than producing identical products, the firms produce slightly different
    products. The difference might be slight, and they might even be just perceived, but they matter, at least
    somewhat, to the consumer. Think about hair stylists and barbers, for example. Some people have certain
    people they like to cut their hair. Some people do not care but might still base their purchasing decision on
    proximity or availability. These differentiations introduce a slight amount of pricing power into the market. The
    differentiations also give rise to the need for firms to advertise what it is about their product that sets them
    apart from competitors. Differentiation can also be a feature of oligopolies.

    Oligopolies are a lot like monopolies except there are some firms, not one, in the market. Think of it this way,
    if you can name the firms that account for a strong majority of the market share off the top of your head, the
    industry is an oligopoly. Oil/Gas companies, airlines, and automobile companies are examples of oligopoly
    markets. The barriers to entry are high but not insurmountable. This feature leads to strategic behavior
    between the firms as the action of one firm affects the outcomes of other firms in the market. Strategic
    behavior will be an important topic explored in future units.

    Reference

    Reynolds, S. S., & Rietzke, D. (2018). Price caps, oligopoly, and entry. Economic Theory, 66(3), 707–745.

    https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc
    t=true&db=bsu&AN=132338488&site=ehost-live&scope=site

    **## EconomicsforManagersECO6301UnitIVJournal.docx**

    2

    Economics for Managers ECO 6301

    **Unit IV Journal**

    This journal measures your mastery of ULOs 1.3, 3.1, 5.1, and 6.3.

    **Journal objective:** International trade can have significant effects on domestic markets. For use in the assignment, identify a good that the United States imports and a good the United States exports.

    **Length:** Your submission is required to be at least 2-pages and not more than 5 pages in length, not including the title page and references.

    **References:** A minimum of 3 peer-reviewed references are required, any additional resources used are required to be scholarly/academic in nature and found in the CSU Library. APA formatting is required to be used for citations and references. Use this definition to define the term in the instructions.

    **Definitions:** Scholarly journals are sometimes called academic journals. The terms are often used interchangeably to describe the same type of publication. These types of publications are published by universities, academic institutions, professional associations, and commercial enterprises and are compiled by scholars, academics, and other subject authorities.

    **Details:** In your paper, include the following:

    · Introduction

    · supply or demand for the particular good,

    · the competitiveness of that good’s market, and

    · how the change in competitiveness affects market structure as well as equilibrium price and quantity.

    · Stepping away from the import/export examples, describe how opening up to trade specifically affects a domestic monopoly. Include an explanation, using game theory, of how even a single additional competitor can lead to a market outcome similar to perfect competition.

    · Conclusion

    **## UnitIVStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit IV

    At the end of this unit, you should be able to:

    5. Apply game theory to pricing and to output decisions in an oligopoly market.
    5.1 Explain how game theory can lead to fierce competition even with only a few competitors in a

    market.

    6. Analyze the basis of trade.
    6.3 Describe how countries opening to international trade affect the market structure of domestic

    industries.

    Required Unit Resources

    Chapter 11: Foreign Exchange, Trade, and Bubbles (ULO 6.3)

    Chapter 15: Strategic Games (ULO 5.1)

    Chapter 16: Bargaining (ULO 5.1)

    Unit Lesson

    Lesson: International Trade and Strategic Behavior (ULOs 5.1, 6.3)
    This lesson will introduce you to the topics of international trade and strategic behavior that are the focus of
    this unit.

    Trade goes back to the dawn of civilization. As travel has become easier and more accessible, international
    trade has connected regions from across the globe. Unit I introduced the benefits of trade with the Starburst
    example. The same benefits hold when the exchange crosses international borders.

    In the Starburst example, the benefits of trade arose from differences in flavor preferences. Generally
    speaking, the benefits of trade arise from differences in opportunity costs. The opportunity costs are not about
    what we give up when we consume, but what we give up when we produce. That is, there are differences in
    production capabilities between people, regions, and countries. Iowa and Nebraska, for example are well
    equipped for producing corn. Colombia is well equipped for producing coffee. Countries with large populations
    and limited capital are well equipped for producing labor intensive goods. Countries with smaller populations
    but more capital are well equipped for producing capital intensive goods.

    If a Country Can Be Self-Sufficient, Should it Be?

    Even if a country can produce everything it needs, it is still better off trading due to differences in opportunity
    costs. Opportunity costs are the value of what you give up when making a choice. The United States might be
    able to produce bananas, but the resources required to produce enough bananas for the entire population
    could be used to produce other things. Producing enough bananas would take more land. Producing enough
    bananas would likely take more buildings and energy to create the proper tropical climate to grow bananas.
    This would all take resources away from producing corn or cars. The labor required to grow more bananas
    would also take labor away from software development or education. Growing bananas in the United States
    would mean giving up a lot of corn (or cars or software development or education), but producing corn (or
    cars or software or education) would not result in losing much banana production.

    UNIT IV STUDY GUIDE
    International Trade and Strategic Behavior

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Having a lower opportunity cost to produce a certain good is called having a comparative advantage in that
    good. Basing production on comparative advantage leads to more overall production that can then be traded
    for other goods. In addition to benefiting from a lower opportunity cost, focusing production on specific goods
    also allows for specialization so producers get even better at producing their goods. By specializing, people
    get better at their tasks and also have time to develop new and better ways of producing. If people are trying
    to produce multiple things, they cannot put the same level of attention into improving specific processes. You
    might be familiar with the phrase “a jack of all trades, but a master of none.” That is what happens without
    specialization.

    Despite the benefits of trade, fear of international trade is common. There are concerns that jobs are lost to
    foreign competition. Certainly, there are specific jobs that will no longer be needed domestically. If the United
    States, for example, had been self-sufficiently producing bananas and then opened up to international trade
    and started importing bananas, jobs in the banana production market would no longer be needed. That does
    not mean, however, that overall jobs are lost to international trade. Jobs are gained from the ability to export
    goods. Jobs are also gained because the resources that were previously used to grow bananas can now be
    used to produce other goods. Also, the lower prices for bananas enable consumers to redirect their spending
    to other goods.

    Trade Protection

    What you might have picked up from the example of the bananas is that despite the benefits of trade, banana
    producers would still have a strong incentive to prevent competition from foreign banana producers. Banana
    producers then have an incentive to lobby the government for protection from foreign competition. This
    protection usually comes in the form of tariffs (there are other forms of trade protection, such as quotas, but
    tariffs are by far the most common).

    Tariffs are in the news a lot, particularly between China and the United States in 2019. Basic economic theory
    tells us that tariffs are simply passed on to consumers. This is not, however, what we necessarily see in
    practice. Elasticity is an important determinant in tax incidence (that is, who bears the burden of a tax). Tax
    incidence is determined by the relative elasticities between supply and demand. From a trade perspective,
    exchange rates can serve as a way for countries to absorb the tariff without having to raise their prices. China
    lets their currency depreciate to keep the prices of their products the same. When this happens, anybody
    holding Chinese currency essentially pays the tariff. Of course, that does not mean there are not costs to the
    United States from assessing tariffs. When China devalues their currency, U.S. produced goods become
    more expensive in China, so quantity demanded for U.S. exports goes down. Ultimately, both countries bear
    some of the burden from tariffs.

    So why assess tariffs? The most obvious reason is as described above: to help domestic interest groups.
    There can be other reasons, however, and to see that, we have to introduce some game theory.

    Game Theory

    Game theory is applied to decision-making where one party’s actions affect another party’s outcome. Game
    theory is not applicable to perfectly competitive markets because individual producers cannot affect the
    market outcome. Game theory is not applicable to monopoly because there is only one producer in a
    monopoly. Game theory is applicable to oligopolies where there are a handful of producers; so what one
    producer does affects the other producers.

    If Coke, for example, comes out with a new product, that new product will likely affect Pepsi and Dr Pepper.
    If Coke changes their price or embarks on a new marketing campaign, Pepsi and Dr Pepper will likely be
    affected. Pepsi and Dr Pepper, thus, need to decide how they will respond to Coke’s actions. Coke will also
    need to anticipate Pepsi and Dr Pepper’s response when deciding the action they take (you can think of it
    like the Battle of Wits from The Princess Bride). The optimal strategy for a “game” is determined by
    evaluating likely strategies by opponents and expected outcomes. Optimal strategies can also be affected
    by the structure of a game. Some games are sequential, where one player makes a decision and then the
    other player makes a decision in response to the first player’s decision. Other games are simultaneous
    where players make their decision at the same time. Ultimately, the outcome of a game is driven by the
    likely outcomes.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Game theory can also be applied to bargaining situations, for example, when bargaining over trade
    agreements. Trade agreements are often termed “free trade agreements,” but that is a bit of a misnomer.
    Certainly, most trade agreements eliminate tariffs, but if that is all that was involved, the agreement could be
    written on a cocktail napkin. Instead, trade agreements often include restrictions or allowances for subsidies,
    requirement wages, environmental rules, and rules of origin (rules of origin are requirements on the countries
    where intermediate goods in the production process were produced). All of these requirements can move the
    agreement away from free trade.

    This is where game theory and bargaining can play a role. Consider trade between the United States and
    China. China places considerable trade restrictions on imports from the United States, and the United States
    has historically not put many on imports from China. Now, per trade theory, this is still beneficial to the United
    States. That is, the United States still benefits from getting goods produced at a lower cost than companies in
    the United States could produce them. The United States would benefit even more, however, if China did not
    have trade restrictions. China, however, feels they benefit from their trade restrictions (standard economic
    theory would say they do not).

    So how does the United States get China to reduce their trade restrictions?

    One possible approach is to employ trade restrictions against Chinese products. This can be thought of as a
    game of chicken, except where the costs are steeper for China than for the United States. The risk, of course,
    for the United States, is that the costs are actually steeper for the United States.

    There are other factors that can matter for a negotiation as well. You might be familiar with the phrase,
    “Whoever gives a number first, loses.” That would suggest that being a first mover could put a bargainer at a
    disadvantage. This is because moving first reveals information to your opponent that they can use to decide
    the action. Credibility to commit to a position matters too. In a repeated game, if one party cannot credibly
    stick to their position through multiple iterations of a game, then the other party can benefit by simply waiting
    out the other party. In the case of the United States and China, the frequency of elections can be a handicap.
    The Chinese government will likely be in power for the foreseeable future, while any given United States
    administration only has certainty of four years at a time to be in power. Fortunately, you can see a lot of these
    concepts play out in the real world by paying attention to the news.

    **## UnitIIIStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit III

    At the end of this unit, you should be able to:

    1. Evaluate the ethical outcomes of free market outcomes using supply and demand models.
    1.3 Compare and contrast the effect perfect competition and monopoly have on total welfare.

    3. Analyze how price and output influence profit maximization under different market structures.

    3.1 Compare and contrast the market outcomes for perfect competition, monopoly, oligopoly, and
    monopolistic competition.

    Required Unit Resources

    Chapter 8: Understanding Markets and Industry Changes (ULO 3.1)

    Chapter 9: Market Structure and Long-Run Equilibrium (ULO 3.1)

    Chapter 10: Strategy: The Quest to Keep Profit from Eroding (ULO 1.3)

    Article: Price Caps, Oligopoly, and Entry (ULO 3.1)

    Unit Lesson

    Unit Material (ULO 2.1)
    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    Supply and Demand

    In a market, supply and demand come together to determine the equilibrium price and quantity. When demand
    increases, price and quantity increase. When supply increases price decreases and quantity increases.

    UNIT III STUDY GUIDE
    Market Structures and Profit

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Demand

    There are several factors that can cause demand to change. Economists group these reasons into five
    main factors:

    Businesses need to know not just these factors but how these factors affect the industry of their business.

    Changes in income, for example, do not affect all businesses the same. Economists categorize goods as
    normal goods, which are goods whose demand increases as income increases, and inferior goods, which are
    goods whose demand increases as income decreases. An example of a normal good would be eating out.
    The more income a person has, the more likely they are to eat at restaurants rather than prepare meals at
    home. Candy, possibly surprisingly, is an inferior good. When people experience lower incomes, they cannot
    afford as much entertainment as before, so candy offers an inexpensive pleasure.

    Changes in the price of related goods is another factor that can have different effects based on specific
    circumstances. Some goods are related in consumption. These are called complements. Peanut butter and
    jelly are an example of complements. If the price of a complement decreases (say, peanut butter), then the
    demand for the good in question (say, jelly) will go up. After all, if you are buying more peanut butter, you are
    going to need more jelly to go with it. Substitutes are goods that compete in consumption. Coke and Dr
    Pepper, for example, are substitutes. If the price of Coke goes down, consumers are more likely to buy Coke,
    and, thus, less likely to buy Dr Pepper. So if the price of a substitute good decreases, the demand for the
    good in question goes down.

    Most of the remaining factors work as might be expected. If the number of demands increases, demand for a
    particular good will increase. Imagine sitting in a waiting room as your oil gets changed. There is a vending
    machine there. You might be tempted to get something. If another person walks into the waiting room, they
    will also be tempted to get something. As more and more people enter the waiting room, the likelihood that
    somebody will purchase from the vending machine increases. Most likely, multiple people will make a
    purchase from the vending machine. In other words, demand will increase.

    Add in tastes and preferences. If a particular product becomes popular (perhaps because of positive press,
    perhaps the product is seasonal, perhaps the product has experienced a change in quality), then more people
    are likely to want the product. In other words, demand increases.

    Finally, look at expectations. Expectations might be a little confusing. The important thing to remember is that
    when looking at the effects of changes in demand, the time frame is immediate. That is, the expectation is for
    some time in the future, but the analysis is what happens to demand right now. So, if consumers expect
    prices to increase in the future, they will want to buy more before prices rise. That is, demand will increase.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Supply

    There are also factors that can affect supply (as opposed to demand). Most of these factors are pretty straight
    forward. As the price of inputs increase, costs to the producers go up, so naturally the supply will decrease.
    For example, if the price of oranges goes up, the supply of orange juice will decrease.

    If the price of a similarly produced product increases, then the supply of the good in question will decrease.
    For example, if looking at the supply of vanilla ice cream and the price of chocolate ice cream increases, then
    the supply of vanilla ice cream will decrease as the resources used to make vanilla ice cream will be shifted
    over to make more chocolate ice cream to take advantage of the higher price.

    As with demand, the number of suppliers matters to supply. The more suppliers there are, the more
    production there is. This is fairly simple and straightforward.

    Technology is also an important factor for supply. An improvement in technology that makes production
    easier and cheaper will lead to an increase in the supply. It is unlikely that a firm would actually adopt new
    technology unless it had the express purpose of making production easier or cheaper. For example, self-
    checkout kiosks at grocery stores or fast food restaurants are technology that make the production process
    (or service delivery process) cheaper for companies. They do require an upfront investment in technology, but
    the payoff is lower operating costs in the future.

    Finally, expectations are important for supply and the same caution that applied to expectations with demand
    apply here. Firms respond now to expectations about the future. Another important note is that while it can
    often be easy to think of supply as production, it is better defined as what producers bring to market. So, if
    producers expect a price decrease in the future, they will want to rush to market what they can to take
    advantage of the relatively higher price. That is, the expectation of a future price decrease will result in an
    increase in supply right now.

    To learn how to draw a supply and demand graph in Microsoft Word, view the video How to Graph in Word.
    You can access closed-captioning once you access the video.

    Market Structure

    As mentioned in the beginning of the lesson, underlying the supply curve is the market structure. Economists
    differentiate market structures (identified by name later in the course) based on three characteristics. Those
    three characteristics are:

    • the number of sellers in a market (The number of buyers matters too, but that does not change
    among these four market structures.);

    • the homogeneity of production (This means how different the production is from one producer to the
    next; another way to think about this is whether you can identify the producer based on the product.);
    and

    • the existence, or not, of barriers to entry (also phrased free entry and exit).

    At one extreme of the market structures is perfect competition. Perfect competition is characterized by:

    • lots of sellers,
    • selling identical products, and
    • no barriers to entry (free entry and exit).

    At the other extreme of market structures is monopoly. Monopoly is characterized by:

    • one producer—and only one (If it is even two producers, it is a different market structure.),
    • selling a product that is unique in the market such that there are no close substitutes, and
    • impossible for competitors to enter.

    As you can see from the characteristics, monopoly is the opposite of perfect competition. These differences
    lead to some important outcomes for the different markets.

    ECO 6301, Economics for Managers 4

    UNIT x STUDY GUIDE
    Title

    Since there are many producers producing exactly the same thing, perfectly competitive firms do not have
    any influence on the overall market. They are very much a “drop in the bucket” relative to the market.
    Perfectly competitive firms must accept whatever the market price is. Monopolies, on the other hand, are the
    only supplier in their market, so their decisions have a big influence on the market outcome. Monopolists
    cannot exactly set their price; they must be mindful of their consumers. When deciding what price to set,
    monopolists have to balance the revenue they would gain from raising their prices with the revenue they
    would lose by selling a lower quantity (and vice versa if they are considering a price decrease).

    Without barriers to entry, if a firm can make excessive profits (known as economic profit), then other firms will
    enter the market, taking some of that profit away. Monopolies are protected by barriers to entry, so if they can
    earn large economic profits, there will not be any competition to come along and take those profits away.

    Perfectly competitive markets are the most efficient. They must be. If a firm is not as efficient as possible, it
    will be run out of the market. Monopolies do not need to be efficient since they are protected by barriers to
    entry. Monopolists, just like every firm, want to maximize profits. Maximizing profit for a monopolist, however,
    means not producing as much as they could so that they can charge a higher price.

    In between these extremes are monopolistic competition and oligopoly. Monopolistic competition is a lot like
    perfect competition, except that rather than producing identical products, the firms produce slightly different
    products. The difference might be slight, and they might even be just perceived, but they matter, at least
    somewhat, to the consumer. Think about hair stylists and barbers, for example. Some people have certain
    people they like to cut their hair. Some people do not care but might still base their purchasing decision on
    proximity or availability. These differentiations introduce a slight amount of pricing power into the market. The
    differentiations also give rise to the need for firms to advertise what it is about their product that sets them
    apart from competitors. Differentiation can also be a feature of oligopolies.

    Oligopolies are a lot like monopolies except there are some firms, not one, in the market. Think of it this way,
    if you can name the firms that account for a strong majority of the market share off the top of your head, the
    industry is an oligopoly. Oil/Gas companies, airlines, and automobile companies are examples of oligopoly
    markets. The barriers to entry are high but not insurmountable. This feature leads to strategic behavior
    between the firms as the action of one firm affects the outcomes of other firms in the market. Strategic
    behavior will be an important topic explored in future units.

    Reference

    Reynolds, S. S., & Rietzke, D. (2018). Price caps, oligopoly, and entry. Economic Theory, 66(3), 707–745.

    https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc
    t=true&db=bsu&AN=132338488&site=ehost-live&scope=site

    **## EconomicsforManagersECO6301UnitIVJournal.docx**

    2

    Economics for Managers ECO 6301

    **Unit IV Journal**

    This journal measures your mastery of ULOs 1.3, 3.1, 5.1, and 6.3.

    **Journal objective:** International trade can have significant effects on domestic markets. For use in the assignment, identify a good that the United States imports and a good the United States exports.

    **Length:** Your submission is required to be at least 2-pages and not more than 5 pages in length, not including the title page and references.

    **References:** A minimum of 3 peer-reviewed references are required, any additional resources used are required to be scholarly/academic in nature and found in the CSU Library. APA formatting is required to be used for citations and references. Use this definition to define the term in the instructions.

    **Definitions:** Scholarly journals are sometimes called academic journals. The terms are often used interchangeably to describe the same type of publication. These types of publications are published by universities, academic institutions, professional associations, and commercial enterprises and are compiled by scholars, academics, and other subject authorities.

    **Details:** In your paper, include the following:

    · Introduction

    · supply or demand for the particular good,

    · the competitiveness of that good’s market, and

    · how the change in competitiveness affects market structure as well as equilibrium price and quantity.

    · Stepping away from the import/export examples, describe how opening up to trade specifically affects a domestic monopoly. Include an explanation, using game theory, of how even a single additional competitor can lead to a market outcome similar to perfect competition.

    · Conclusion

    **## UnitIVStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit IV

    At the end of this unit, you should be able to:

    5. Apply game theory to pricing and to output decisions in an oligopoly market.
    5.1 Explain how game theory can lead to fierce competition even with only a few competitors in a

    market.

    6. Analyze the basis of trade.
    6.3 Describe how countries opening to international trade affect the market structure of domestic

    industries.

    Required Unit Resources

    Chapter 11: Foreign Exchange, Trade, and Bubbles (ULO 6.3)

    Chapter 15: Strategic Games (ULO 5.1)

    Chapter 16: Bargaining (ULO 5.1)

    Unit Lesson

    Lesson: International Trade and Strategic Behavior (ULOs 5.1, 6.3)
    This lesson will introduce you to the topics of international trade and strategic behavior that are the focus of
    this unit.

    Trade goes back to the dawn of civilization. As travel has become easier and more accessible, international
    trade has connected regions from across the globe. Unit I introduced the benefits of trade with the Starburst
    example. The same benefits hold when the exchange crosses international borders.

    In the Starburst example, the benefits of trade arose from differences in flavor preferences. Generally
    speaking, the benefits of trade arise from differences in opportunity costs. The opportunity costs are not about
    what we give up when we consume, but what we give up when we produce. That is, there are differences in
    production capabilities between people, regions, and countries. Iowa and Nebraska, for example are well
    equipped for producing corn. Colombia is well equipped for producing coffee. Countries with large populations
    and limited capital are well equipped for producing labor intensive goods. Countries with smaller populations
    but more capital are well equipped for producing capital intensive goods.

    If a Country Can Be Self-Sufficient, Should it Be?

    Even if a country can produce everything it needs, it is still better off trading due to differences in opportunity
    costs. Opportunity costs are the value of what you give up when making a choice. The United States might be
    able to produce bananas, but the resources required to produce enough bananas for the entire population
    could be used to produce other things. Producing enough bananas would take more land. Producing enough
    bananas would likely take more buildings and energy to create the proper tropical climate to grow bananas.
    This would all take resources away from producing corn or cars. The labor required to grow more bananas
    would also take labor away from software development or education. Growing bananas in the United States
    would mean giving up a lot of corn (or cars or software development or education), but producing corn (or
    cars or software or education) would not result in losing much banana production.

    UNIT IV STUDY GUIDE
    International Trade and Strategic Behavior

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Having a lower opportunity cost to produce a certain good is called having a comparative advantage in that
    good. Basing production on comparative advantage leads to more overall production that can then be traded
    for other goods. In addition to benefiting from a lower opportunity cost, focusing production on specific goods
    also allows for specialization so producers get even better at producing their goods. By specializing, people
    get better at their tasks and also have time to develop new and better ways of producing. If people are trying
    to produce multiple things, they cannot put the same level of attention into improving specific processes. You
    might be familiar with the phrase “a jack of all trades, but a master of none.” That is what happens without
    specialization.

    Despite the benefits of trade, fear of international trade is common. There are concerns that jobs are lost to
    foreign competition. Certainly, there are specific jobs that will no longer be needed domestically. If the United
    States, for example, had been self-sufficiently producing bananas and then opened up to international trade
    and started importing bananas, jobs in the banana production market would no longer be needed. That does
    not mean, however, that overall jobs are lost to international trade. Jobs are gained from the ability to export
    goods. Jobs are also gained because the resources that were previously used to grow bananas can now be
    used to produce other goods. Also, the lower prices for bananas enable consumers to redirect their spending
    to other goods.

    Trade Protection

    What you might have picked up from the example of the bananas is that despite the benefits of trade, banana
    producers would still have a strong incentive to prevent competition from foreign banana producers. Banana
    producers then have an incentive to lobby the government for protection from foreign competition. This
    protection usually comes in the form of tariffs (there are other forms of trade protection, such as quotas, but
    tariffs are by far the most common).

    Tariffs are in the news a lot, particularly between China and the United States in 2019. Basic economic theory
    tells us that tariffs are simply passed on to consumers. This is not, however, what we necessarily see in
    practice. Elasticity is an important determinant in tax incidence (that is, who bears the burden of a tax). Tax
    incidence is determined by the relative elasticities between supply and demand. From a trade perspective,
    exchange rates can serve as a way for countries to absorb the tariff without having to raise their prices. China
    lets their currency depreciate to keep the prices of their products the same. When this happens, anybody
    holding Chinese currency essentially pays the tariff. Of course, that does not mean there are not costs to the
    United States from assessing tariffs. When China devalues their currency, U.S. produced goods become
    more expensive in China, so quantity demanded for U.S. exports goes down. Ultimately, both countries bear
    some of the burden from tariffs.

    So why assess tariffs? The most obvious reason is as described above: to help domestic interest groups.
    There can be other reasons, however, and to see that, we have to introduce some game theory.

    Game Theory

    Game theory is applied to decision-making where one party’s actions affect another party’s outcome. Game
    theory is not applicable to perfectly competitive markets because individual producers cannot affect the
    market outcome. Game theory is not applicable to monopoly because there is only one producer in a
    monopoly. Game theory is applicable to oligopolies where there are a handful of producers; so what one
    producer does affects the other producers.

    If Coke, for example, comes out with a new product, that new product will likely affect Pepsi and Dr Pepper.
    If Coke changes their price or embarks on a new marketing campaign, Pepsi and Dr Pepper will likely be
    affected. Pepsi and Dr Pepper, thus, need to decide how they will respond to Coke’s actions. Coke will also
    need to anticipate Pepsi and Dr Pepper’s response when deciding the action they take (you can think of it
    like the Battle of Wits from The Princess Bride). The optimal strategy for a “game” is determined by
    evaluating likely strategies by opponents and expected outcomes. Optimal strategies can also be affected
    by the structure of a game. Some games are sequential, where one player makes a decision and then the
    other player makes a decision in response to the first player’s decision. Other games are simultaneous
    where players make their decision at the same time. Ultimately, the outcome of a game is driven by the
    likely outcomes.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Game theory can also be applied to bargaining situations, for example, when bargaining over trade
    agreements. Trade agreements are often termed “free trade agreements,” but that is a bit of a misnomer.
    Certainly, most trade agreements eliminate tariffs, but if that is all that was involved, the agreement could be
    written on a cocktail napkin. Instead, trade agreements often include restrictions or allowances for subsidies,
    requirement wages, environmental rules, and rules of origin (rules of origin are requirements on the countries
    where intermediate goods in the production process were produced). All of these requirements can move the
    agreement away from free trade.

    This is where game theory and bargaining can play a role. Consider trade between the United States and
    China. China places considerable trade restrictions on imports from the United States, and the United States
    has historically not put many on imports from China. Now, per trade theory, this is still beneficial to the United
    States. That is, the United States still benefits from getting goods produced at a lower cost than companies in
    the United States could produce them. The United States would benefit even more, however, if China did not
    have trade restrictions. China, however, feels they benefit from their trade restrictions (standard economic
    theory would say they do not).

    So how does the United States get China to reduce their trade restrictions?

    One possible approach is to employ trade restrictions against Chinese products. This can be thought of as a
    game of chicken, except where the costs are steeper for China than for the United States. The risk, of course,
    for the United States, is that the costs are actually steeper for the United States.

    There are other factors that can matter for a negotiation as well. You might be familiar with the phrase,
    “Whoever gives a number first, loses.” That would suggest that being a first mover could put a bargainer at a
    disadvantage. This is because moving first reveals information to your opponent that they can use to decide
    the action. Credibility to commit to a position matters too. In a repeated game, if one party cannot credibly
    stick to their position through multiple iterations of a game, then the other party can benefit by simply waiting
    out the other party. In the case of the United States and China, the frequency of elections can be a handicap.
    The Chinese government will likely be in power for the foreseeable future, while any given United States
    administration only has certainty of four years at a time to be in power. Fortunately, you can see a lot of these
    concepts play out in the real world by paying attention to the news.

    **## UnitIIIStudyGuide.pdf**

    ECO 6301, Economics for Managers 1

    Course Learning Outcomes for Unit III

    At the end of this unit, you should be able to:

    1. Evaluate the ethical outcomes of free market outcomes using supply and demand models.
    1.3 Compare and contrast the effect perfect competition and monopoly have on total welfare.

    3. Analyze how price and output influence profit maximization under different market structures.

    3.1 Compare and contrast the market outcomes for perfect competition, monopoly, oligopoly, and
    monopolistic competition.

    Required Unit Resources

    Chapter 8: Understanding Markets and Industry Changes (ULO 3.1)

    Chapter 9: Market Structure and Long-Run Equilibrium (ULO 3.1)

    Chapter 10: Strategy: The Quest to Keep Profit from Eroding (ULO 1.3)

    Article: Price Caps, Oligopoly, and Entry (ULO 3.1)

    Unit Lesson

    Unit Material (ULO 2.1)
    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    This unit’s material focuses on different types of market structures and how firms in those markets seek profit.
    Before getting into market structures, we will discuss a bit about markets in general. All markets are affected
    by supply and demand. The type of market structure in question will primarily affect how supply behaves, but
    important information for firms comes from demand.

    Supply and Demand

    In a market, supply and demand come together to determine the equilibrium price and quantity. When demand
    increases, price and quantity increase. When supply increases price decreases and quantity increases.

    UNIT III STUDY GUIDE
    Market Structures and Profit

    ECO 6301, Economics for Managers 2

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Demand

    There are several factors that can cause demand to change. Economists group these reasons into five
    main factors:

    Businesses need to know not just these factors but how these factors affect the industry of their business.

    Changes in income, for example, do not affect all businesses the same. Economists categorize goods as
    normal goods, which are goods whose demand increases as income increases, and inferior goods, which are
    goods whose demand increases as income decreases. An example of a normal good would be eating out.
    The more income a person has, the more likely they are to eat at restaurants rather than prepare meals at
    home. Candy, possibly surprisingly, is an inferior good. When people experience lower incomes, they cannot
    afford as much entertainment as before, so candy offers an inexpensive pleasure.

    Changes in the price of related goods is another factor that can have different effects based on specific
    circumstances. Some goods are related in consumption. These are called complements. Peanut butter and
    jelly are an example of complements. If the price of a complement decreases (say, peanut butter), then the
    demand for the good in question (say, jelly) will go up. After all, if you are buying more peanut butter, you are
    going to need more jelly to go with it. Substitutes are goods that compete in consumption. Coke and Dr
    Pepper, for example, are substitutes. If the price of Coke goes down, consumers are more likely to buy Coke,
    and, thus, less likely to buy Dr Pepper. So if the price of a substitute good decreases, the demand for the
    good in question goes down.

    Most of the remaining factors work as might be expected. If the number of demands increases, demand for a
    particular good will increase. Imagine sitting in a waiting room as your oil gets changed. There is a vending
    machine there. You might be tempted to get something. If another person walks into the waiting room, they
    will also be tempted to get something. As more and more people enter the waiting room, the likelihood that
    somebody will purchase from the vending machine increases. Most likely, multiple people will make a
    purchase from the vending machine. In other words, demand will increase.

    Add in tastes and preferences. If a particular product becomes popular (perhaps because of positive press,
    perhaps the product is seasonal, perhaps the product has experienced a change in quality), then more people
    are likely to want the product. In other words, demand increases.

    Finally, look at expectations. Expectations might be a little confusing. The important thing to remember is that
    when looking at the effects of changes in demand, the time frame is immediate. That is, the expectation is for
    some time in the future, but the analysis is what happens to demand right now. So, if consumers expect
    prices to increase in the future, they will want to buy more before prices rise. That is, demand will increase.

    ECO 6301, Economics for Managers 3

    UNIT x STUDY GUIDE
    Title

    Factors Affecting Supply

    There are also factors that can affect supply (as opposed to demand). Most of these factors are pretty straight
    forward. As the price of inputs increase, costs to the producers go up, so naturally the supply will decrease.
    For example, if the price of oranges goes up, the supply of orange juice will decrease.

    If the price of a similarly produced product increases, then the supply of the good in question will decrease.
    For example, if looking at the supply of vanilla ice cream and the price of chocolate ice cream increases, then
    the supply of vanilla ice cream will decrease as the resources used to make vanilla ice cream will be shifted
    over to make more chocolate ice cream to take advantage of the higher price.

    As with demand, the number of suppliers matters to supply. The more suppliers there are, the more
    production there is. This is fairly simple and straightforward.

    Technology is also an important factor for supply. An improvement in technology that makes production
    easier and cheaper will lead to an increase in the supply. It is unlikely that a firm would actually adopt new
    technology unless it had the express purpose of making production easier or cheaper. For example, self-
    checkout kiosks at grocery stores or fast food restaurants are technology that make the production process
    (or service delivery process) cheaper for companies. They do require an upfront investment in technology, but
    the payoff is lower operating costs in the future.

    Finally, expectations are important for supply and the same caution that applied to expectations with demand
    apply here. Firms respond now to expectations about the future. Another important note is that while it can
    often be easy to think of supply as production, it is better defined as what producers bring to market. So, if
    producers expect a price decrease in the future, they will want to rush to market what they can to take
    advantage of the relatively higher price. That is, the expectation of a future price decrease will result in an
    increase in supply right now.

    To learn how to draw a supply and demand graph in Microsoft Word, view the video How to Graph in Word.
    You can access closed-captioning once you access the video.

    Market Structure

    As mentioned in the beginning of the lesson, underlying the supply curve is the market structure. Economists
    differentiate market structures (identified by name later in the course) based on three characteristics. Those
    three characteristics are:

    • the number of sellers in a market (The number of buyers matters too, but that does not change
    among these four market structures.);

    • the homogeneity of production (This means how different the production is from one producer to the
    next; another way to think about this is whether you can identify the producer based on the product.);
    and

    • the existence, or not, of barriers to entry (also phrased free entry and exit).

    At one extreme of the market structures is perfect competition. Perfect competition is characterized by:

    • lots of sellers,
    • selling identical products, and
    • no barriers to entry (free entry and exit).

    At the other extreme of market structures is monopoly. Monopoly is characterized by:

    • one producer—and only one (If it is even two producers, it is a different market structure.),
    • selling a product that is unique in the market such that there are no close substitutes, and
    • impossible for competitors to enter.

    As you can see from the characteristics, monopoly is the opposite of perfect competition. These differences
    lead to some important outcomes for the different markets.

    ECO 6301, Economics for Managers 4

    UNIT x STUDY GUIDE
    Title

    Since there are many producers producing exactly the same thing, perfectly competitive firms do not have
    any influence on the overall market. They are very much a “drop in the bucket” relative to the market.
    Perfectly competitive firms must accept whatever the market price is. Monopolies, on the other hand, are the
    only supplier in their market, so their decisions have a big influence on the market outcome. Monopolists
    cannot exactly set their price; they must be mindful of their consumers. When deciding what price to set,
    monopolists have to balance the revenue they would gain from raising their prices with the revenue they
    would lose by selling a lower quantity (and vice versa if they are considering a price decrease).

    Without barriers to entry, if a firm can make excessive profits (known as economic profit), then other firms will
    enter the market, taking some of that profit away. Monopolies are protected by barriers to entry, so if they can
    earn large economic profits, there will not be any competition to come along and take those profits away.

    Perfectly competitive markets are the most efficient. They must be. If a firm is not as efficient as possible, it
    will be run out of the market. Monopolies do not need to be efficient since they are protected by barriers to
    entry. Monopolists, just like every firm, want to maximize profits. Maximizing profit for a monopolist, however,
    means not producing as much as they could so that they can charge a higher price.

    In between these extremes are monopolistic competition and oligopoly. Monopolistic competition is a lot like
    perfect competition, except that rather than producing identical products, the firms produce slightly different
    products. The difference might be slight, and they might even be just perceived, but they matter, at least
    somewhat, to the consumer. Think about hair stylists and barbers, for example. Some people have certain
    people they like to cut their hair. Some people do not care but might still base their purchasing decision on
    proximity or availability. These differentiations introduce a slight amount of pricing power into the market. The
    differentiations also give rise to the need for firms to advertise what it is about their product that sets them
    apart from competitors. Differentiation can also be a feature of oligopolies.

    Oligopolies are a lot like monopolies except there are some firms, not one, in the market. Think of it this way,
    if you can name the firms that account for a strong majority of the market share off the top of your head, the
    industry is an oligopoly. Oil/Gas companies, airlines, and automobile companies are examples of oligopoly
    markets. The barriers to entry are high but not insurmountable. This feature leads to strategic behavior
    between the firms as the action of one firm affects the outcomes of other firms in the market. Strategic
    behavior will be an important topic explored in future units.

    Reference

    Reynolds, S. S., & Rietzke, D. (2018). Price caps, oligopoly, and entry. Economic Theory, 66(3), 707–745.

    https://libraryresources.columbiasouthern.edu/login?url=http://search.ebscohost.com/login.aspx?direc
    t=true&db=bsu&AN=132338488&site=ehost-live&scope=site

    – 1
    – 2
    – 3

  • [Solved] 5-1 Final Project Milestone Two: Budget Proposal Spreadsheet

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    For this task, you will submit the proposed budget and rationale for your final project assignment.

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    For this task, you will submit the proposed budget and rationale for your final project assignment.

  • [Solved] Business Finance – Management Writing Assignment 2

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    Use the film as a case example to explore broader themes in global supply chain and logistics. **:** Watch the film _Captain Phillips_

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    Use the film as a case example to explore broader themes in global supply chain and logistics. **:**
    Watch the film _Captain Phillips_

  • [Solved] A – Discussion Thread: Farrington Medical Devices

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    **Discussion Thread: Farrington Medical Devices** At the end of Chapter 4, please read the Farrington Medical Devices Case Study and respond to all three of the case questions.

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    **Discussion Thread: Farrington Medical Devices**
    At the end of Chapter 4, please read the Farrington Medical Devices Case Study and respond to all three of the case questions.

  • [Solved] Unit VII Ess

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    se attached – ## UnitVIIEssa1.docx **## UnitVIIEssa1.docx** Unit VII Essay Choose a well-known global organization (e.g., Amazon, McDonald’s, Zara, Unilever) that operates in multiple international markets. Research how the chosen organization distributes its products across different markets. Consi…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    se attached

    – ## UnitVIIEssa1.docx

    **## UnitVIIEssa1.docx**

    Unit VII Essay

    Choose a well-known global organization (e.g., Amazon, McDonald’s, Zara, Unilever) that operates in multiple international markets. Research how the chosen organization distributes its products across different markets. Consider both physical (retail, wholesale) and digital (e-commerce, direct-to-consumer) channels. Describe the marketing distribution channels and explain whether you would change the distribution channels or not. Include any challenges the company is facing with distribution strategies and provide potential solutions. Include a description of key logistical aspects such as warehousing, inventory management, transportation, and supply chain coordination.

    Begin with an introduction. Your essay least one page in length, not counting the reference page. You must use at least one source to support your essay. Follow APA Style when creating citations and references for this assignment.

    **## UnitVIIEssa1.docx**

    Unit VII Essay

    Choose a well-known global organization (e.g., Amazon, McDonald’s, Zara, Unilever) that operates in multiple international markets. Research how the chosen organization distributes its products across different markets. Consider both physical (retail, wholesale) and digital (e-commerce, direct-to-consumer) channels. Describe the marketing distribution channels and explain whether you would change the distribution channels or not. Include any challenges the company is facing with distribution strategies and provide potential solutions. Include a description of key logistical aspects such as warehousing, inventory management, transportation, and supply chain coordination.

    Begin with an introduction. Your essay least one page in length, not counting the reference page. You must use at least one source to support your essay. Follow APA Style when creating citations and references for this assignment.

  • [Solved] RCH 5301 DB PP

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    – ## ResearchDesignandMethodsRCH5301UnitIIDBPeerPost.docx **## ResearchDesignandMethodsRCH5301UnitIIDBPeerPost.docx** 2 Research Design and Methods RCH 5301 **Unit II DB** Then, select a peer post and evaluate the appropriateness of using a quantitative research strategy for their proposed study. Di…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    – ## ResearchDesignandMethodsRCH5301UnitIIDBPeerPost.docx

    **## ResearchDesignandMethodsRCH5301UnitIIDBPeerPost.docx**

    2

    Research Design and Methods RCH 5301

    **Unit II DB**

    Then, select a peer post and evaluate the appropriateness of using a quantitative research strategy for their proposed study. Discuss challenges they might encounter using a quantitative methodology.

    Peer Post Below

    Top of Form

    Workforce and force management are crucial areas in any organization, since they deal with the effective use of human resources. A quantitative research study can shed light on these areas, helping leaders to make better decisions. Understanding the importance of labor and force management is essential because it directly affects productivity and efficiency. For example, if an organization does not have enough qualified workers, it could have difficulty fulfilling its objectives, which leads to mission failure and decreased motivation among existing employees.

    Choosing the quantitative methodology is rational for this type of study because it allows researchers to collect numerical data that can be analyzed statistically. This method provides clear evidence to support the findings,

    which is especially important to make strategic decisions in labor management. According to Zhang (2023), quantitative approaches facilitate the evaluation of complex structures, ensuring an exhaustive analysis of human resources management. Through the use of surveys or experiments, researchers can collect

    data in large quantities, which makes it easier to identify trends and patterns that may not be notable through qualitative methods.

    The evaluation of the quantitative approach for labor management can shed light on best practices and improvement areas. For example, if you conducted a study using statistical analysis to measure the performance and satisfaction of employees, we can evaluate the effectiveness of their methodology. However, potential challenges may arise. A challenge could be the need for precise data, since biased or incomplete data can lead to deceptive conclusions. Another challenge is to ensure that the sample size is large enough to support generalizable findings, since small samples may not represent the largest population effectively.

    In summary, analyzing a quantitative research study on labor and strength management is significant to understand organizational efficiency. The use of a quantitative methodology helps reveal important trends and supports solid decision making. The evaluation of peer approaches can provide information, but researchers must be aware of possible challenges related to data collection and sample sizes. In general, as organizations strive for better labor management, take advantage of quantitative research remains a key factor in achieving

    success (Zhang, 2023).

    **Citations:**

    Zhang,

    H. (2023). Fuzzy comprehensive evaluation and quantitative weight analysis in

    structure management of human resources. PLoS One, 18(7), e0288795.
    [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288795](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288795)

    Bottom of Form

    Reply

    It should be at least 300 words in length.

    It should include at least one APA-formatted scholarly, professional, or textbook reference with accompanying in-text citation to support any paraphrased, summarized, or quoted material.

    **## ResearchDesignandMethodsRCH5301UnitIIDBPeerPost.docx**

    2

    Research Design and Methods RCH 5301

    **Unit II DB**

    Then, select a peer post and evaluate the appropriateness of using a quantitative research strategy for their proposed study. Discuss challenges they might encounter using a quantitative methodology.

    Peer Post Below

    Top of Form

    Workforce and force management are crucial areas in any organization, since they deal with the effective use of human resources. A quantitative research study can shed light on these areas, helping leaders to make better decisions. Understanding the importance of labor and force management is essential because it directly affects productivity and efficiency. For example, if an organization does not have enough qualified workers, it could have difficulty fulfilling its objectives, which leads to mission failure and decreased motivation among existing employees.

    Choosing the quantitative methodology is rational for this type of study because it allows researchers to collect numerical data that can be analyzed statistically. This method provides clear evidence to support the findings,

    which is especially important to make strategic decisions in labor management. According to Zhang (2023), quantitative approaches facilitate the evaluation of complex structures, ensuring an exhaustive analysis of human resources management. Through the use of surveys or experiments, researchers can collect

    data in large quantities, which makes it easier to identify trends and patterns that may not be notable through qualitative methods.

    The evaluation of the quantitative approach for labor management can shed light on best practices and improvement areas. For example, if you conducted a study using statistical analysis to measure the performance and satisfaction of employees, we can evaluate the effectiveness of their methodology. However, potential challenges may arise. A challenge could be the need for precise data, since biased or incomplete data can lead to deceptive conclusions. Another challenge is to ensure that the sample size is large enough to support generalizable findings, since small samples may not represent the largest population effectively.

    In summary, analyzing a quantitative research study on labor and strength management is significant to understand organizational efficiency. The use of a quantitative methodology helps reveal important trends and supports solid decision making. The evaluation of peer approaches can provide information, but researchers must be aware of possible challenges related to data collection and sample sizes. In general, as organizations strive for better labor management, take advantage of quantitative research remains a key factor in achieving

    success (Zhang, 2023).

    **Citations:**

    Zhang,

    H. (2023). Fuzzy comprehensive evaluation and quantitative weight analysis in

    structure management of human resources. PLoS One, 18(7), e0288795.
    [https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288795](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0288795)

    Bottom of Form

    Reply

    It should be at least 300 words in length.

    It should include at least one APA-formatted scholarly, professional, or textbook reference with accompanying in-text citation to support any paraphrased, summarized, or quoted material.

  • [Solved] RCH 5301 III

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    – ## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx – ## UnitIIStudyGuide.pdf – UnitIIIStudyGuide.pdf **## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx** 2 Research Design and Methods RCH 5301 **Unit III Assignment** This self-completion questionnair…

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    – ## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx

    – ## UnitIIStudyGuide.pdf

    – UnitIIIStudyGuide.pdf

    **## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx**

    2

    Research Design and Methods RCH 5301

    **Unit III Assignment**

    This self-completion questionnaire measures your mastery of ULOs 4.1 and 4.2.

    **Self-Completion Questionnaire**

    For this assignment, you will create a self-completion questionnaire for the quantitative research project of interest you described in the Unit II discussion board. As discussed in the Unit III study guide, a self-completion questionnaire should be comprised of three parts: 1) the cover, 2) the instructions, and 3) the survey items. Construct these three parts by responding to the following prompts:

    Part 1 The Survey Cover

    · State the problem(s) to be solved.

    · Describe the population of interest.

    · Explain how you would determine sample size.

    · Define the sampling frame.

    · State the sampling design. (i.e., type of sampling)

    · Explain if the survey will be cross-sectional or longitudinal.

    · Detail how the surveys will be distributed and collected upon completion.

    2 The Survey Instructions

    · Create clear and unambiguous survey instructions for participants, in familiar language, that explain how to complete the questionnaire.

    Part 3 The Survey Items

    · Formulate eight closed-ended survey questions, using a Likert scale of your choosing, that would help solve your problem(s) when answered.

    · Include a minimum of four closed-ended demographic questions.

    Please thoroughly address all areas listed above and use APA-compliant headings and sub-headings that align with the individual assignment prompts. Respond to the prompts in the same sequence they are requested above and do not combine elements within a section.

    For guidance, refer to the sections on Survey Instrument Design and Advice for Survey Construction in the Unit III study guide. The survey that is developed should appear professional and in a format that would be suitable for distribution to participants.

    Your assignment should consist of a minimum of two pages in length. No references are required unless information is quoted or paraphrased.

    **## UnitIIStudyGuide.pdf**

    RCH 5301, Research Design and Methods 1

    Course Learning Outcomes for Unit II

    At the end of this unit, you should be able to:

    4. Apply research methods within a research design.
    4.1 Explain the relationship of population, sampling frame, sampling design, and

    generalization.

    Required Unit Resources

    Chapter 2: Review of Literature (ULO 4.1)

    Chapter 8: Quantitative Methods (ULO 4.1)
    Read the following sections from this chapter:

    • Introduction
    • Putting Quantitative Research in Context
    • Quantitative Designs

    Video: Discovering Math: Advanced—Statistics and Data Analysis: Part 2 (ULO 4.1)
    Watch the following segments to learn more about data analysis. The transcript for this video can be found by
    clicking on “Transcript” in the gray bar to the right of the video in the Films on Demand database.

    • The Statistics of Sampling, or By Any Means” (Segment 9) (2 minutes)
    • “Sampling Distributions—Elephant Ages” (Segment 10) (2 minutes)
    • “Central Limit Theorem—Giraffe Graphs” (Segment 11) (2 minutes)
    • “Confidence Intervals— Running Cheetahs” (Segment 12) (3 minutes)
    • “Sampling Techniques” (Segment 13) (2 minutes)
    • “Uncertainty in Statistical Inferences” (Segment 17) (2 minutes)
    • “Sampling Error and Confidence Interval—High School Completion” (Segment 18) (2 minutes)
    • “Means— Average Salaries and Education” (Segment 20) (4 minutes)

    Video: Confidence Intervals: Against All Odds—Inside Statistics (ULO 4.1)
    This video touches on many of this unit’s concepts, such as target population, random samples, confidence
    intervals, and solving business problems. The transcript for this video can be found by clicking on “Transcript”
    in the gray bar to the right of the video in the Films on Demand database. (10 minutes).

    Unit Lesson

    Lesson: Sampling and Statistical Inference: Leave the Crystal Ball at Home (ULO 4.1)

    Populations, Samples, and Statistical Inference

    Positivist researchers share the epistemological assumption that knowledge is achieved through observation
    and measurement of phenomena using a quantitative research methodological strategy. Measuring and
    quantifying phenomena can be valuable as an end, such as in descriptive statistics; however, the true
    advantage of using quantitative data is in its ability to be used for statistical inference. In quantitative
    research, statistical inference refers to being able to draw conclusions about a population of interest from
    analyzing sample data selected from the population. Making inferences about a population is also known as
    generalizing results.

    UNIT II STUDY GUIDE
    Sampling, Confidence Intervals,
    and Inferential Statistics

    RCH 5301, Research Design and Methods 2

    UNIT x STUDY GUIDE
    Title

    (Adapted from Zaman, n.d.)

    A population can include virtually anything that can be counted and measured, including human participants,
    objects, and events, and there is no limit to the industries that can apply inferential statistics, including
    business and finance, marketing, law, medicine, health and safety, psychology and sociology, manufacturing,
    logistics, technology, education, energy, and the list goes on. Likewise, the application of inferential statistics
    is endless. For example, sampling can be used to make inferences about the average job satisfaction level of
    a population of employees, to make inferences about the percentage of defects in a population of
    manufactured units, to make inferences about average achievement test scores in a population of elementary
    school students, and to make inferences about the relationship between accident victim fatality rates and
    years of experience of first responders.

    Two of the primary research methods used to facilitate statistical inference in business and social science
    research are sampling and surveying. While immersed in this content on sampling, keep in mind that
    surveying is the most ubiquitous quantitative method used to collect sample data today. Surveying and
    sampling are used because, in many cases, it is simply not feasible from a cost or time perspective to gather
    data from every participant in the population of interest. If that were possible, it would be called a census.
    Rather, the use of sample data is an efficient and cost-effective alternative to make inferences about
    population means, proportions, and relationships between variables. An example of a population mean is the
    average antibody response to a new medicine. An example of a population proportion is the percentage of
    retirement savings for workers who participate in employer-sponsored savings plans. An example of a
    relationship between variables would be the correlation of reported cases of cannabis psychosis and age of
    user. This discussion will focus on the use of samples and confidence intervals to make inferences about
    population means.

    Sampling Error: Random Error Versus Systematic Error

    While sampling can be an efficient and cost-effective alternative to using a census, it is not perfect. A sample
    mean is unlikely to be an exact representative of the population mean. The sample mean could be very close
    to the population mean or not close at all. The variance between the true population mean and the sampling
    mean is due to sampling error. Sampling error takes two forms, which are random error and systematic error.

    RCH 5301, Research Design and Methods 3

    UNIT x STUDY GUIDE
    Title

    Random error, as its name suggests, occurs randomly. The sample mean may not truly represent the
    population mean due to factors like natural variations and individual differences in the cases selected for the
    sample or simply due to pure chance. Random error is unpredictable, so each measurement in the sample
    clusters around the true population mean and moves in both directions, both above and below, as shown in
    the graphic below. Random error can be mitigated, but not eliminated completely, by increasing sample size
    (Zikmund et al., 2013).

    Systematic error is generally non-random and occurs through deficiencies and errors in the process of
    sampling rather than the sample itself. For example, systematic error can occur through researcher errors,
    such as poor survey construction, analytical errors, and bias. As a result, systematic error is predictable, and
    each measurement will move in the same direction relative to the true population mean, either above or
    below, as shown in the graphic. Systematic error is controllable and, therefore, can be substantially reduced
    through improving systematic processes, such as recalibrating measurement equipment and pilot testing
    surveys, but it cannot be mitigated by increasing sample size (Zikmund et al., 2013).

    (Adapted from The Office of Research Integrity, n.d.)

    This discussion of sampling error highlights the imperfection and limitations of sampling. While systematic
    error can be substantially eliminated by a conscientious researcher, random error will always present a
    challenge to predicting population means. Fortunately, sample size and the central limit theorem (discussed
    later in this lesson) can help the researcher minimize random error.

    Statistical Inference Using Confidence Intervals

    Although sampling error will always be a factor in using samples to draw conclusions about population
    means, the power of statistical inference is in its ability to estimate the true values of population means, even
    in the face of random error. One of the most common methods used to make inferences about population
    means is confidence intervals.

    A confidence interval uses a sample to create a range of mean values in which the population mean is likely
    to fall. For example, a sample of emergency calls into a 911 call center may provide an average length of 4.2
    minutes per call. The following confidence intervals can be calculated from this sample:

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    RCH 5301, Research Design and Methods 4

    UNIT x STUDY GUIDE
    Title

    The first confidence interval indicates, with 68.27% confidence, that the population mean lies between 3.8 and
    4.6 minutes. The last confidence interval indicates, with 99.73% confidence, that the population mean lies
    between 3.0 and 5.4. This is useful information, but it is also helpful to have a basic understanding of how
    these statistics were derived.

    The first point to understand is that the confidence interval represents the area of probability in a normally
    distributed data set. The confidence intervals above were used for a very specific reason. A confidence
    interval of 68.27 corresponds to +-1 standard deviation, a confidence interval of 95.45 corresponds to +-2
    standard deviations, and a confidence interval of 99.73 corresponds to +-3 standard deviations. This is
    represented in the distribution graphic below.

    (Weaver, 2016)

    Researchers customarily use the 95% confidence interval when estimating population means from sample
    data. Using a lower confidence interval, such as 68.25%, will give a tighter range in which the population
    mean is estimated to fall, but the confidence is not sufficiently large. A higher confidence interval, such as
    99.73%, will give a wider range in which the population mean is estimated to fall, but the confidence is so
    large that it is not useful in predicting the population parameter (Cooper & Schindler, 2014).

    The second aspect of confidence intervals that is important to understand is a statistic called the standard
    error of the mean (often referred to as the standard error or SE) and something called the Z-score. The
    standard error of the mean can be thought of as the standard deviation of the sample data; more accurately,
    SE is the standard deviation of the sampling distribution, which will be discussed below. As a side note,
    standard deviation (σ) pertains to population data and is called a parameter. The standard error of the mean
    pertains to sample data and is called a statistic. Parameters describe population data, while statistics describe
    sample data. The SE is estimated from the sample standard deviation (s). Some very intelligent statisticians
    determined how to estimate the SE; otherwise, it would be necessary to draw a large number of individual
    samples to create a sampling distribution to calculate the SE. This is discussed further in the section below on
    the Central Limit Theorem. It is not necessary to know how SE is calculated. It is more important for
    practitioners to understand how to use this statistic rather than how to calculate it (Field, 2005; Zikmund et al.,
    2013).

    The Z-score, or standard score, is also integral to calculating confidence intervals. A Z-score uses standard
    deviation to compare a sample mean (�̅�𝑥) to a single data value. A Z-score of 1 indicates that a single data
    value is one standard deviation from �̅�𝑥. The Z-score will be positive if the single data value is above �̅�𝑥, and it
    will be negative if it lies below �̅�𝑥. Z-scores can be found by referring to a Z-score table or using a Z-score
    calculator. Both can be found on the internet. In the example below, a 95% confidence level equates to a Z-
    score of 1.96 or 1.96 standard deviations. As mentioned above, researchers usually use a 95% confidence
    interval, so a Z-Score of 1.96 would always be used. The other examples were included to provide an

    RCH 5301, Research Design and Methods 5

    UNIT x STUDY GUIDE
    Title

    understanding of the area under a normal curve that is included for the respective confidence intervals (see
    bell curve above) and to show the application of the appropriate Z-score based on the confidence interval
    used (Brase & Brase, 2013).

    The following will show how the standard error of the mean and Z-scores were used in the 911 call center
    scenario mentioned above.

    �̅�𝑥 – [(Z) (.4 SE)] ≤ µ ≤ �̅�𝑥 + [(Z) (.4 SE)] = Confidence Interval
    �̅�𝑥 = Sample Mean = 4.2 minutes
    Z = Z Score (Standard Deviation)
    SE = Standard Error of the Mean = .4 minutes
    µ = Population Mean

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    4.2 minutes – [(1) x (.4)] = 3.8 minutes ≤ µ ≤ 4.2 minutes + [(1) x (.4)] = 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    4.2 minutes – [(1.96) x (.4)] = 3.416 minutes ≤ µ ≤ 4.2 minutes + [(1.96) x (.4)] = 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    4.2 minutes – [(2) x (.4)] = 3.4 minutes ≤ µ ≤ 4.2 minutes + [(2) x (.4)] = 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    4.2 minutes – [(3) x (.4)] = 3.0 minutes ≤ µ ≤ 4.2 minutes + [(3) x (.4)] = 5.4 minutes

    Precise confidence intervals and Z-scores (standard deviations) were used in the calculations above. For
    example, a 95% confidence interval equates to a Z-score of 1.96 standard deviations. This means that +-1.96
    standard deviations from the mean represent 95% of the area under a normal curve. Compare this to the
    95.45% confidence interval that equates to a Z-score of 2 standard deviations, representing 95.45% of the
    area under a normal curve. While the Z-scores for the 95% and 95.45% confidence intervals are very close,
    researchers should use the precise Z-score (standard deviation) of 1.96, rather than 2, when calculating a
    95% confidence interval. This warning is provided to help allay any confusion since standard deviations and
    intervals under the normal curve are often simplified in usage. This simplification is referred to as the
    empirical rule, the 68-95-99.7 rule, or the three-sigma rule. For example, 1.96 standard deviations are often
    rounded to two standard deviations to represent 95% of the area under a normal curve. This is fine for quick
    forecasting, but precision is recommended for high stakes calculations (Brase & Brase, 2013; Salkind, 2009).

    The last point that is important to understand is that the confidence interval range depends on both sample
    size and the dispersion of the sample’s data values around the mean. The precision of a confidence interval
    may be increased by increasing the size of the sample. As Bell et al. (2022) comprehensively explain, there is
    an inverse relationship between sample size and sampling error. As sample size increases, the sampling
    error will decrease, and the confidence interval will become tighter and more precise. Gains in precision are
    clearly evident up to sample sizes of around 1,000 cases. After this, precision gains become much less
    noticeable. It should also be noted that it is an absolute—rather than relative—sample size that is important,
    regardless of the size of the population of interest. This means that a researcher should not be concerned
    about taking a certain percentage of the population as a sample. There is little benefit of samples larger than
    1,000, regardless of whether the population size is 1 million or 100 million.

    A larger dispersion of the data values around the sample mean will result in less confidence that the sample
    mean is a better representative of the population mean than a smaller dispersion of data values around the
    sample mean. For example, assume two samples each had a sample mean of 4.2 minutes of average wait
    times. Sample 1 has a range of values from .25 minutes to 15 minutes, while Sample 2 has a range of values
    from 4 minutes to 5 minutes. There would be more confidence that Sample 2’s mean is representative of the
    population mean due to the smaller dispersion of data values, which is reflected in a smaller standard error.

    RCH 5301, Research Design and Methods 6

    UNIT x STUDY GUIDE
    Title

    Figure 1 (Adapted from The University of Florida, n.d.)

    Central Limit Theorem

    In the discussion above about sampling error, it was noted that sampling is not perfect. If Sample 1 is from the
    population, its mean is unlikely to be an exact representative of the population mean. Additionally, if Sample 2
    is drawn from the same population, its mean would likely not represent the population mean or the Sample 1
    mean. If additional samples are drawn from the same population, it is very likely that the means from each
    sample would vary. This begs the question, how well does a single sample represent the population?

    One way to address this conundrum would be to continue to take many individual samples from the
    population. In theory, hundreds or thousands of samples would be taken from the population. For each
    sample, a sample mean (�̅�𝑥) would be calculated, resulting in a collection of many sample means.
    Remarkably, plotting the sample means in a histogram would result in a normal bell-shaped curve, called a
    sampling distribution, even if the population data is not normally distributed! This is beneficial since the
    distribution of the population is often unknown or may be known to be irregular. The central limit theorem says
    that for any population distribution at all, regardless of its shape, the sampling distribution from that population
    will be bell-shaped as long as the sample size is sufficiently large. Statisticians have determined that a
    sample size of n > 30 is sufficient for the central limit theorem to apply. If the population data is close to being
    normally distributed, then smaller sample sizes will result in normal distributions of sample means. If,
    however, the population distribution is far from normal, then larger sample sizes will be needed to ensure a
    normal distribution of sample means (Norusis, 2008).

    In addition to the sampling distribution exhibiting normality, the central limit theorem states that the average of
    the sample means would be a very close, near exact estimate of the population mean and would draw closer
    as the sample size is increased. Fortunately, as mentioned above, the standard deviation of a single sample
    can be used to estimate the standard error of the mean. This alleviates the impracticality of taking many
    samples from the same population to create a sampling distribution. A small standard error indicates that the
    sample mean is a close estimate of the population mean. Conversely, a large standard error would indicate
    that the sample mean is not a close estimate of the population mean. In short, a small standard error is good;
    a large standard error—not so much (Norusis, 2008).

    RCH 5301, Research Design and Methods 7

    UNIT x STUDY GUIDE
    Title

    In Closing

    This unit presented the basics of sampling, including populations, samples, statistical inference and
    generalization, sampling error, and confidence intervals. One simple but important takeaway from this unit
    should be that as sample size increases, sample standard deviation decreases, resulting in the sample mean
    becoming a better estimate of the population mean. Additionally, it is important to remember that sample size
    is absolute rather than relative, and after n = 1,000, the benefits of sample size begin to diminish. Therefore, a
    sample of n = 1,000 would be an optimal sample size for a population that is 1 million or 50 million.

    Unit III will explore the topics of structured interviews, surveys, and questionnaires. These are the data
    collection methods that work together with sampling. Later units will return to the idea of using inferential
    statistics for hypothesis testing.

    References

    Annenberg Learner. (2013). Confidence intervals: Against all odds—Inside statistics [Video]. Films on

    Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=111543

    Bell, E., Bryman, A., & Harley, B. (2022). Business research methods (6th ed.). Oxford University Press.

    https://online.vitalsource.com/#/books/9780192640505

    Brase, C. H., & Brase, C. P. (2013). Understanding basic statistics (6th ed.). Cengage Learning.

    Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.

    Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods

    approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964

    Discovery Education. (2007). Discovering math: Advanced—Statistics and data analysis: Part 2 [Video]. Films

    on Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=117915

    Field, A. (2005). Discovering stats using SPSS (2nd ed.). SAGE.

    Norusis, M. J. (2008). SPSS 16.0 guide to data analysis. Prentice Hall.

    The Office of Research Integrity. (n.d.) Module 4: Method of information collection – Section 2:3 [Graphic].

    https://ori.hhs.gov/node/1228/printable/print

    Salkind, N. J. (2009). Exploring research (7th ed.). Pearson Education.

    The University of Florida. (n.d.). Estimation [Graphic]. https://bolt.mph.ufl.edu/6050-6052/unit-4/module-11/

    Weaver, P. (2016, July 19). Can you use standard deviation in project management? [Chart]. Project

    Manager. https://projectmanager.com.au/can-you-use-standard-deviation-in-project-management/

    Zaman, E. (n.d.) What is the difference between population and sample? [Graphic]. BBA Lectures.

    https://www.bbalectures.com/what-is-the-difference-between-population-and-sample/

    Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage

    Learning.

    **UnitIIIStudyGuide.pdf**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/unitiiistudyguide-pdf-10344473)

    **UnitIIIStudyGuide.pdf**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/unitiiistudyguide-pdf-10344473)

    **## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx**

    2

    Research Design and Methods RCH 5301

    **Unit III Assignment**

    This self-completion questionnaire measures your mastery of ULOs 4.1 and 4.2.

    **Self-Completion Questionnaire**

    For this assignment, you will create a self-completion questionnaire for the quantitative research project of interest you described in the Unit II discussion board. As discussed in the Unit III study guide, a self-completion questionnaire should be comprised of three parts: 1) the cover, 2) the instructions, and 3) the survey items. Construct these three parts by responding to the following prompts:

    Part 1 The Survey Cover

    · State the problem(s) to be solved.

    · Describe the population of interest.

    · Explain how you would determine sample size.

    · Define the sampling frame.

    · State the sampling design. (i.e., type of sampling)

    · Explain if the survey will be cross-sectional or longitudinal.

    · Detail how the surveys will be distributed and collected upon completion.

    2 The Survey Instructions

    · Create clear and unambiguous survey instructions for participants, in familiar language, that explain how to complete the questionnaire.

    Part 3 The Survey Items

    · Formulate eight closed-ended survey questions, using a Likert scale of your choosing, that would help solve your problem(s) when answered.

    · Include a minimum of four closed-ended demographic questions.

    Please thoroughly address all areas listed above and use APA-compliant headings and sub-headings that align with the individual assignment prompts. Respond to the prompts in the same sequence they are requested above and do not combine elements within a section.

    For guidance, refer to the sections on Survey Instrument Design and Advice for Survey Construction in the Unit III study guide. The survey that is developed should appear professional and in a format that would be suitable for distribution to participants.

    Your assignment should consist of a minimum of two pages in length. No references are required unless information is quoted or paraphrased.

    **## UnitIIStudyGuide.pdf**

    RCH 5301, Research Design and Methods 1

    Course Learning Outcomes for Unit II

    At the end of this unit, you should be able to:

    4. Apply research methods within a research design.
    4.1 Explain the relationship of population, sampling frame, sampling design, and

    generalization.

    Required Unit Resources

    Chapter 2: Review of Literature (ULO 4.1)

    Chapter 8: Quantitative Methods (ULO 4.1)
    Read the following sections from this chapter:

    • Introduction
    • Putting Quantitative Research in Context
    • Quantitative Designs

    Video: Discovering Math: Advanced—Statistics and Data Analysis: Part 2 (ULO 4.1)
    Watch the following segments to learn more about data analysis. The transcript for this video can be found by
    clicking on “Transcript” in the gray bar to the right of the video in the Films on Demand database.

    • The Statistics of Sampling, or By Any Means” (Segment 9) (2 minutes)
    • “Sampling Distributions—Elephant Ages” (Segment 10) (2 minutes)
    • “Central Limit Theorem—Giraffe Graphs” (Segment 11) (2 minutes)
    • “Confidence Intervals— Running Cheetahs” (Segment 12) (3 minutes)
    • “Sampling Techniques” (Segment 13) (2 minutes)
    • “Uncertainty in Statistical Inferences” (Segment 17) (2 minutes)
    • “Sampling Error and Confidence Interval—High School Completion” (Segment 18) (2 minutes)
    • “Means— Average Salaries and Education” (Segment 20) (4 minutes)

    Video: Confidence Intervals: Against All Odds—Inside Statistics (ULO 4.1)
    This video touches on many of this unit’s concepts, such as target population, random samples, confidence
    intervals, and solving business problems. The transcript for this video can be found by clicking on “Transcript”
    in the gray bar to the right of the video in the Films on Demand database. (10 minutes).

    Unit Lesson

    Lesson: Sampling and Statistical Inference: Leave the Crystal Ball at Home (ULO 4.1)

    Populations, Samples, and Statistical Inference

    Positivist researchers share the epistemological assumption that knowledge is achieved through observation
    and measurement of phenomena using a quantitative research methodological strategy. Measuring and
    quantifying phenomena can be valuable as an end, such as in descriptive statistics; however, the true
    advantage of using quantitative data is in its ability to be used for statistical inference. In quantitative
    research, statistical inference refers to being able to draw conclusions about a population of interest from
    analyzing sample data selected from the population. Making inferences about a population is also known as
    generalizing results.

    UNIT II STUDY GUIDE
    Sampling, Confidence Intervals,
    and Inferential Statistics

    RCH 5301, Research Design and Methods 2

    UNIT x STUDY GUIDE
    Title

    (Adapted from Zaman, n.d.)

    A population can include virtually anything that can be counted and measured, including human participants,
    objects, and events, and there is no limit to the industries that can apply inferential statistics, including
    business and finance, marketing, law, medicine, health and safety, psychology and sociology, manufacturing,
    logistics, technology, education, energy, and the list goes on. Likewise, the application of inferential statistics
    is endless. For example, sampling can be used to make inferences about the average job satisfaction level of
    a population of employees, to make inferences about the percentage of defects in a population of
    manufactured units, to make inferences about average achievement test scores in a population of elementary
    school students, and to make inferences about the relationship between accident victim fatality rates and
    years of experience of first responders.

    Two of the primary research methods used to facilitate statistical inference in business and social science
    research are sampling and surveying. While immersed in this content on sampling, keep in mind that
    surveying is the most ubiquitous quantitative method used to collect sample data today. Surveying and
    sampling are used because, in many cases, it is simply not feasible from a cost or time perspective to gather
    data from every participant in the population of interest. If that were possible, it would be called a census.
    Rather, the use of sample data is an efficient and cost-effective alternative to make inferences about
    population means, proportions, and relationships between variables. An example of a population mean is the
    average antibody response to a new medicine. An example of a population proportion is the percentage of
    retirement savings for workers who participate in employer-sponsored savings plans. An example of a
    relationship between variables would be the correlation of reported cases of cannabis psychosis and age of
    user. This discussion will focus on the use of samples and confidence intervals to make inferences about
    population means.

    Sampling Error: Random Error Versus Systematic Error

    While sampling can be an efficient and cost-effective alternative to using a census, it is not perfect. A sample
    mean is unlikely to be an exact representative of the population mean. The sample mean could be very close
    to the population mean or not close at all. The variance between the true population mean and the sampling
    mean is due to sampling error. Sampling error takes two forms, which are random error and systematic error.

    RCH 5301, Research Design and Methods 3

    UNIT x STUDY GUIDE
    Title

    Random error, as its name suggests, occurs randomly. The sample mean may not truly represent the
    population mean due to factors like natural variations and individual differences in the cases selected for the
    sample or simply due to pure chance. Random error is unpredictable, so each measurement in the sample
    clusters around the true population mean and moves in both directions, both above and below, as shown in
    the graphic below. Random error can be mitigated, but not eliminated completely, by increasing sample size
    (Zikmund et al., 2013).

    Systematic error is generally non-random and occurs through deficiencies and errors in the process of
    sampling rather than the sample itself. For example, systematic error can occur through researcher errors,
    such as poor survey construction, analytical errors, and bias. As a result, systematic error is predictable, and
    each measurement will move in the same direction relative to the true population mean, either above or
    below, as shown in the graphic. Systematic error is controllable and, therefore, can be substantially reduced
    through improving systematic processes, such as recalibrating measurement equipment and pilot testing
    surveys, but it cannot be mitigated by increasing sample size (Zikmund et al., 2013).

    (Adapted from The Office of Research Integrity, n.d.)

    This discussion of sampling error highlights the imperfection and limitations of sampling. While systematic
    error can be substantially eliminated by a conscientious researcher, random error will always present a
    challenge to predicting population means. Fortunately, sample size and the central limit theorem (discussed
    later in this lesson) can help the researcher minimize random error.

    Statistical Inference Using Confidence Intervals

    Although sampling error will always be a factor in using samples to draw conclusions about population
    means, the power of statistical inference is in its ability to estimate the true values of population means, even
    in the face of random error. One of the most common methods used to make inferences about population
    means is confidence intervals.

    A confidence interval uses a sample to create a range of mean values in which the population mean is likely
    to fall. For example, a sample of emergency calls into a 911 call center may provide an average length of 4.2
    minutes per call. The following confidence intervals can be calculated from this sample:

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    RCH 5301, Research Design and Methods 4

    UNIT x STUDY GUIDE
    Title

    The first confidence interval indicates, with 68.27% confidence, that the population mean lies between 3.8 and
    4.6 minutes. The last confidence interval indicates, with 99.73% confidence, that the population mean lies
    between 3.0 and 5.4. This is useful information, but it is also helpful to have a basic understanding of how
    these statistics were derived.

    The first point to understand is that the confidence interval represents the area of probability in a normally
    distributed data set. The confidence intervals above were used for a very specific reason. A confidence
    interval of 68.27 corresponds to +-1 standard deviation, a confidence interval of 95.45 corresponds to +-2
    standard deviations, and a confidence interval of 99.73 corresponds to +-3 standard deviations. This is
    represented in the distribution graphic below.

    (Weaver, 2016)

    Researchers customarily use the 95% confidence interval when estimating population means from sample
    data. Using a lower confidence interval, such as 68.25%, will give a tighter range in which the population
    mean is estimated to fall, but the confidence is not sufficiently large. A higher confidence interval, such as
    99.73%, will give a wider range in which the population mean is estimated to fall, but the confidence is so
    large that it is not useful in predicting the population parameter (Cooper & Schindler, 2014).

    The second aspect of confidence intervals that is important to understand is a statistic called the standard
    error of the mean (often referred to as the standard error or SE) and something called the Z-score. The
    standard error of the mean can be thought of as the standard deviation of the sample data; more accurately,
    SE is the standard deviation of the sampling distribution, which will be discussed below. As a side note,
    standard deviation (σ) pertains to population data and is called a parameter. The standard error of the mean
    pertains to sample data and is called a statistic. Parameters describe population data, while statistics describe
    sample data. The SE is estimated from the sample standard deviation (s). Some very intelligent statisticians
    determined how to estimate the SE; otherwise, it would be necessary to draw a large number of individual
    samples to create a sampling distribution to calculate the SE. This is discussed further in the section below on
    the Central Limit Theorem. It is not necessary to know how SE is calculated. It is more important for
    practitioners to understand how to use this statistic rather than how to calculate it (Field, 2005; Zikmund et al.,
    2013).

    The Z-score, or standard score, is also integral to calculating confidence intervals. A Z-score uses standard
    deviation to compare a sample mean (�̅�𝑥) to a single data value. A Z-score of 1 indicates that a single data
    value is one standard deviation from �̅�𝑥. The Z-score will be positive if the single data value is above �̅�𝑥, and it
    will be negative if it lies below �̅�𝑥. Z-scores can be found by referring to a Z-score table or using a Z-score
    calculator. Both can be found on the internet. In the example below, a 95% confidence level equates to a Z-
    score of 1.96 or 1.96 standard deviations. As mentioned above, researchers usually use a 95% confidence
    interval, so a Z-Score of 1.96 would always be used. The other examples were included to provide an

    RCH 5301, Research Design and Methods 5

    UNIT x STUDY GUIDE
    Title

    understanding of the area under a normal curve that is included for the respective confidence intervals (see
    bell curve above) and to show the application of the appropriate Z-score based on the confidence interval
    used (Brase & Brase, 2013).

    The following will show how the standard error of the mean and Z-scores were used in the 911 call center
    scenario mentioned above.

    �̅�𝑥 – [(Z) (.4 SE)] ≤ µ ≤ �̅�𝑥 + [(Z) (.4 SE)] = Confidence Interval
    �̅�𝑥 = Sample Mean = 4.2 minutes
    Z = Z Score (Standard Deviation)
    SE = Standard Error of the Mean = .4 minutes
    µ = Population Mean

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    4.2 minutes – [(1) x (.4)] = 3.8 minutes ≤ µ ≤ 4.2 minutes + [(1) x (.4)] = 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    4.2 minutes – [(1.96) x (.4)] = 3.416 minutes ≤ µ ≤ 4.2 minutes + [(1.96) x (.4)] = 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    4.2 minutes – [(2) x (.4)] = 3.4 minutes ≤ µ ≤ 4.2 minutes + [(2) x (.4)] = 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    4.2 minutes – [(3) x (.4)] = 3.0 minutes ≤ µ ≤ 4.2 minutes + [(3) x (.4)] = 5.4 minutes

    Precise confidence intervals and Z-scores (standard deviations) were used in the calculations above. For
    example, a 95% confidence interval equates to a Z-score of 1.96 standard deviations. This means that +-1.96
    standard deviations from the mean represent 95% of the area under a normal curve. Compare this to the
    95.45% confidence interval that equates to a Z-score of 2 standard deviations, representing 95.45% of the
    area under a normal curve. While the Z-scores for the 95% and 95.45% confidence intervals are very close,
    researchers should use the precise Z-score (standard deviation) of 1.96, rather than 2, when calculating a
    95% confidence interval. This warning is provided to help allay any confusion since standard deviations and
    intervals under the normal curve are often simplified in usage. This simplification is referred to as the
    empirical rule, the 68-95-99.7 rule, or the three-sigma rule. For example, 1.96 standard deviations are often
    rounded to two standard deviations to represent 95% of the area under a normal curve. This is fine for quick
    forecasting, but precision is recommended for high stakes calculations (Brase & Brase, 2013; Salkind, 2009).

    The last point that is important to understand is that the confidence interval range depends on both sample
    size and the dispersion of the sample’s data values around the mean. The precision of a confidence interval
    may be increased by increasing the size of the sample. As Bell et al. (2022) comprehensively explain, there is
    an inverse relationship between sample size and sampling error. As sample size increases, the sampling
    error will decrease, and the confidence interval will become tighter and more precise. Gains in precision are
    clearly evident up to sample sizes of around 1,000 cases. After this, precision gains become much less
    noticeable. It should also be noted that it is an absolute—rather than relative—sample size that is important,
    regardless of the size of the population of interest. This means that a researcher should not be concerned
    about taking a certain percentage of the population as a sample. There is little benefit of samples larger than
    1,000, regardless of whether the population size is 1 million or 100 million.

    A larger dispersion of the data values around the sample mean will result in less confidence that the sample
    mean is a better representative of the population mean than a smaller dispersion of data values around the
    sample mean. For example, assume two samples each had a sample mean of 4.2 minutes of average wait
    times. Sample 1 has a range of values from .25 minutes to 15 minutes, while Sample 2 has a range of values
    from 4 minutes to 5 minutes. There would be more confidence that Sample 2’s mean is representative of the
    population mean due to the smaller dispersion of data values, which is reflected in a smaller standard error.

    RCH 5301, Research Design and Methods 6

    UNIT x STUDY GUIDE
    Title

    Figure 1 (Adapted from The University of Florida, n.d.)

    Central Limit Theorem

    In the discussion above about sampling error, it was noted that sampling is not perfect. If Sample 1 is from the
    population, its mean is unlikely to be an exact representative of the population mean. Additionally, if Sample 2
    is drawn from the same population, its mean would likely not represent the population mean or the Sample 1
    mean. If additional samples are drawn from the same population, it is very likely that the means from each
    sample would vary. This begs the question, how well does a single sample represent the population?

    One way to address this conundrum would be to continue to take many individual samples from the
    population. In theory, hundreds or thousands of samples would be taken from the population. For each
    sample, a sample mean (�̅�𝑥) would be calculated, resulting in a collection of many sample means.
    Remarkably, plotting the sample means in a histogram would result in a normal bell-shaped curve, called a
    sampling distribution, even if the population data is not normally distributed! This is beneficial since the
    distribution of the population is often unknown or may be known to be irregular. The central limit theorem says
    that for any population distribution at all, regardless of its shape, the sampling distribution from that population
    will be bell-shaped as long as the sample size is sufficiently large. Statisticians have determined that a
    sample size of n > 30 is sufficient for the central limit theorem to apply. If the population data is close to being
    normally distributed, then smaller sample sizes will result in normal distributions of sample means. If,
    however, the population distribution is far from normal, then larger sample sizes will be needed to ensure a
    normal distribution of sample means (Norusis, 2008).

    In addition to the sampling distribution exhibiting normality, the central limit theorem states that the average of
    the sample means would be a very close, near exact estimate of the population mean and would draw closer
    as the sample size is increased. Fortunately, as mentioned above, the standard deviation of a single sample
    can be used to estimate the standard error of the mean. This alleviates the impracticality of taking many
    samples from the same population to create a sampling distribution. A small standard error indicates that the
    sample mean is a close estimate of the population mean. Conversely, a large standard error would indicate
    that the sample mean is not a close estimate of the population mean. In short, a small standard error is good;
    a large standard error—not so much (Norusis, 2008).

    RCH 5301, Research Design and Methods 7

    UNIT x STUDY GUIDE
    Title

    In Closing

    This unit presented the basics of sampling, including populations, samples, statistical inference and
    generalization, sampling error, and confidence intervals. One simple but important takeaway from this unit
    should be that as sample size increases, sample standard deviation decreases, resulting in the sample mean
    becoming a better estimate of the population mean. Additionally, it is important to remember that sample size
    is absolute rather than relative, and after n = 1,000, the benefits of sample size begin to diminish. Therefore, a
    sample of n = 1,000 would be an optimal sample size for a population that is 1 million or 50 million.

    Unit III will explore the topics of structured interviews, surveys, and questionnaires. These are the data
    collection methods that work together with sampling. Later units will return to the idea of using inferential
    statistics for hypothesis testing.

    References

    Annenberg Learner. (2013). Confidence intervals: Against all odds—Inside statistics [Video]. Films on

    Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=111543

    Bell, E., Bryman, A., & Harley, B. (2022). Business research methods (6th ed.). Oxford University Press.

    https://online.vitalsource.com/#/books/9780192640505

    Brase, C. H., & Brase, C. P. (2013). Understanding basic statistics (6th ed.). Cengage Learning.

    Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.

    Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods

    approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964

    Discovery Education. (2007). Discovering math: Advanced—Statistics and data analysis: Part 2 [Video]. Films

    on Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=117915

    Field, A. (2005). Discovering stats using SPSS (2nd ed.). SAGE.

    Norusis, M. J. (2008). SPSS 16.0 guide to data analysis. Prentice Hall.

    The Office of Research Integrity. (n.d.) Module 4: Method of information collection – Section 2:3 [Graphic].

    https://ori.hhs.gov/node/1228/printable/print

    Salkind, N. J. (2009). Exploring research (7th ed.). Pearson Education.

    The University of Florida. (n.d.). Estimation [Graphic]. https://bolt.mph.ufl.edu/6050-6052/unit-4/module-11/

    Weaver, P. (2016, July 19). Can you use standard deviation in project management? [Chart]. Project

    Manager. https://projectmanager.com.au/can-you-use-standard-deviation-in-project-management/

    Zaman, E. (n.d.) What is the difference between population and sample? [Graphic]. BBA Lectures.

    https://www.bbalectures.com/what-is-the-difference-between-population-and-sample/

    Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage

    Learning.

    **UnitIIIStudyGuide.pdf**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/unitiiistudyguide-pdf-10344473)

    **## ResearchDesignandMethodsRCH5301UnitIIISelfCompletionQuestionnaire.docx**

    2

    Research Design and Methods RCH 5301

    **Unit III Assignment**

    This self-completion questionnaire measures your mastery of ULOs 4.1 and 4.2.

    **Self-Completion Questionnaire**

    For this assignment, you will create a self-completion questionnaire for the quantitative research project of interest you described in the Unit II discussion board. As discussed in the Unit III study guide, a self-completion questionnaire should be comprised of three parts: 1) the cover, 2) the instructions, and 3) the survey items. Construct these three parts by responding to the following prompts:

    Part 1 The Survey Cover

    · State the problem(s) to be solved.

    · Describe the population of interest.

    · Explain how you would determine sample size.

    · Define the sampling frame.

    · State the sampling design. (i.e., type of sampling)

    · Explain if the survey will be cross-sectional or longitudinal.

    · Detail how the surveys will be distributed and collected upon completion.

    2 The Survey Instructions

    · Create clear and unambiguous survey instructions for participants, in familiar language, that explain how to complete the questionnaire.

    Part 3 The Survey Items

    · Formulate eight closed-ended survey questions, using a Likert scale of your choosing, that would help solve your problem(s) when answered.

    · Include a minimum of four closed-ended demographic questions.

    Please thoroughly address all areas listed above and use APA-compliant headings and sub-headings that align with the individual assignment prompts. Respond to the prompts in the same sequence they are requested above and do not combine elements within a section.

    For guidance, refer to the sections on Survey Instrument Design and Advice for Survey Construction in the Unit III study guide. The survey that is developed should appear professional and in a format that would be suitable for distribution to participants.

    Your assignment should consist of a minimum of two pages in length. No references are required unless information is quoted or paraphrased.

    **## UnitIIStudyGuide.pdf**

    RCH 5301, Research Design and Methods 1

    Course Learning Outcomes for Unit II

    At the end of this unit, you should be able to:

    4. Apply research methods within a research design.
    4.1 Explain the relationship of population, sampling frame, sampling design, and

    generalization.

    Required Unit Resources

    Chapter 2: Review of Literature (ULO 4.1)

    Chapter 8: Quantitative Methods (ULO 4.1)
    Read the following sections from this chapter:

    • Introduction
    • Putting Quantitative Research in Context
    • Quantitative Designs

    Video: Discovering Math: Advanced—Statistics and Data Analysis: Part 2 (ULO 4.1)
    Watch the following segments to learn more about data analysis. The transcript for this video can be found by
    clicking on “Transcript” in the gray bar to the right of the video in the Films on Demand database.

    • The Statistics of Sampling, or By Any Means” (Segment 9) (2 minutes)
    • “Sampling Distributions—Elephant Ages” (Segment 10) (2 minutes)
    • “Central Limit Theorem—Giraffe Graphs” (Segment 11) (2 minutes)
    • “Confidence Intervals— Running Cheetahs” (Segment 12) (3 minutes)
    • “Sampling Techniques” (Segment 13) (2 minutes)
    • “Uncertainty in Statistical Inferences” (Segment 17) (2 minutes)
    • “Sampling Error and Confidence Interval—High School Completion” (Segment 18) (2 minutes)
    • “Means— Average Salaries and Education” (Segment 20) (4 minutes)

    Video: Confidence Intervals: Against All Odds—Inside Statistics (ULO 4.1)
    This video touches on many of this unit’s concepts, such as target population, random samples, confidence
    intervals, and solving business problems. The transcript for this video can be found by clicking on “Transcript”
    in the gray bar to the right of the video in the Films on Demand database. (10 minutes).

    Unit Lesson

    Lesson: Sampling and Statistical Inference: Leave the Crystal Ball at Home (ULO 4.1)

    Populations, Samples, and Statistical Inference

    Positivist researchers share the epistemological assumption that knowledge is achieved through observation
    and measurement of phenomena using a quantitative research methodological strategy. Measuring and
    quantifying phenomena can be valuable as an end, such as in descriptive statistics; however, the true
    advantage of using quantitative data is in its ability to be used for statistical inference. In quantitative
    research, statistical inference refers to being able to draw conclusions about a population of interest from
    analyzing sample data selected from the population. Making inferences about a population is also known as
    generalizing results.

    UNIT II STUDY GUIDE
    Sampling, Confidence Intervals,
    and Inferential Statistics

    RCH 5301, Research Design and Methods 2

    UNIT x STUDY GUIDE
    Title

    (Adapted from Zaman, n.d.)

    A population can include virtually anything that can be counted and measured, including human participants,
    objects, and events, and there is no limit to the industries that can apply inferential statistics, including
    business and finance, marketing, law, medicine, health and safety, psychology and sociology, manufacturing,
    logistics, technology, education, energy, and the list goes on. Likewise, the application of inferential statistics
    is endless. For example, sampling can be used to make inferences about the average job satisfaction level of
    a population of employees, to make inferences about the percentage of defects in a population of
    manufactured units, to make inferences about average achievement test scores in a population of elementary
    school students, and to make inferences about the relationship between accident victim fatality rates and
    years of experience of first responders.

    Two of the primary research methods used to facilitate statistical inference in business and social science
    research are sampling and surveying. While immersed in this content on sampling, keep in mind that
    surveying is the most ubiquitous quantitative method used to collect sample data today. Surveying and
    sampling are used because, in many cases, it is simply not feasible from a cost or time perspective to gather
    data from every participant in the population of interest. If that were possible, it would be called a census.
    Rather, the use of sample data is an efficient and cost-effective alternative to make inferences about
    population means, proportions, and relationships between variables. An example of a population mean is the
    average antibody response to a new medicine. An example of a population proportion is the percentage of
    retirement savings for workers who participate in employer-sponsored savings plans. An example of a
    relationship between variables would be the correlation of reported cases of cannabis psychosis and age of
    user. This discussion will focus on the use of samples and confidence intervals to make inferences about
    population means.

    Sampling Error: Random Error Versus Systematic Error

    While sampling can be an efficient and cost-effective alternative to using a census, it is not perfect. A sample
    mean is unlikely to be an exact representative of the population mean. The sample mean could be very close
    to the population mean or not close at all. The variance between the true population mean and the sampling
    mean is due to sampling error. Sampling error takes two forms, which are random error and systematic error.

    RCH 5301, Research Design and Methods 3

    UNIT x STUDY GUIDE
    Title

    Random error, as its name suggests, occurs randomly. The sample mean may not truly represent the
    population mean due to factors like natural variations and individual differences in the cases selected for the
    sample or simply due to pure chance. Random error is unpredictable, so each measurement in the sample
    clusters around the true population mean and moves in both directions, both above and below, as shown in
    the graphic below. Random error can be mitigated, but not eliminated completely, by increasing sample size
    (Zikmund et al., 2013).

    Systematic error is generally non-random and occurs through deficiencies and errors in the process of
    sampling rather than the sample itself. For example, systematic error can occur through researcher errors,
    such as poor survey construction, analytical errors, and bias. As a result, systematic error is predictable, and
    each measurement will move in the same direction relative to the true population mean, either above or
    below, as shown in the graphic. Systematic error is controllable and, therefore, can be substantially reduced
    through improving systematic processes, such as recalibrating measurement equipment and pilot testing
    surveys, but it cannot be mitigated by increasing sample size (Zikmund et al., 2013).

    (Adapted from The Office of Research Integrity, n.d.)

    This discussion of sampling error highlights the imperfection and limitations of sampling. While systematic
    error can be substantially eliminated by a conscientious researcher, random error will always present a
    challenge to predicting population means. Fortunately, sample size and the central limit theorem (discussed
    later in this lesson) can help the researcher minimize random error.

    Statistical Inference Using Confidence Intervals

    Although sampling error will always be a factor in using samples to draw conclusions about population
    means, the power of statistical inference is in its ability to estimate the true values of population means, even
    in the face of random error. One of the most common methods used to make inferences about population
    means is confidence intervals.

    A confidence interval uses a sample to create a range of mean values in which the population mean is likely
    to fall. For example, a sample of emergency calls into a 911 call center may provide an average length of 4.2
    minutes per call. The following confidence intervals can be calculated from this sample:

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    RCH 5301, Research Design and Methods 4

    UNIT x STUDY GUIDE
    Title

    The first confidence interval indicates, with 68.27% confidence, that the population mean lies between 3.8 and
    4.6 minutes. The last confidence interval indicates, with 99.73% confidence, that the population mean lies
    between 3.0 and 5.4. This is useful information, but it is also helpful to have a basic understanding of how
    these statistics were derived.

    The first point to understand is that the confidence interval represents the area of probability in a normally
    distributed data set. The confidence intervals above were used for a very specific reason. A confidence
    interval of 68.27 corresponds to +-1 standard deviation, a confidence interval of 95.45 corresponds to +-2
    standard deviations, and a confidence interval of 99.73 corresponds to +-3 standard deviations. This is
    represented in the distribution graphic below.

    (Weaver, 2016)

    Researchers customarily use the 95% confidence interval when estimating population means from sample
    data. Using a lower confidence interval, such as 68.25%, will give a tighter range in which the population
    mean is estimated to fall, but the confidence is not sufficiently large. A higher confidence interval, such as
    99.73%, will give a wider range in which the population mean is estimated to fall, but the confidence is so
    large that it is not useful in predicting the population parameter (Cooper & Schindler, 2014).

    The second aspect of confidence intervals that is important to understand is a statistic called the standard
    error of the mean (often referred to as the standard error or SE) and something called the Z-score. The
    standard error of the mean can be thought of as the standard deviation of the sample data; more accurately,
    SE is the standard deviation of the sampling distribution, which will be discussed below. As a side note,
    standard deviation (σ) pertains to population data and is called a parameter. The standard error of the mean
    pertains to sample data and is called a statistic. Parameters describe population data, while statistics describe
    sample data. The SE is estimated from the sample standard deviation (s). Some very intelligent statisticians
    determined how to estimate the SE; otherwise, it would be necessary to draw a large number of individual
    samples to create a sampling distribution to calculate the SE. This is discussed further in the section below on
    the Central Limit Theorem. It is not necessary to know how SE is calculated. It is more important for
    practitioners to understand how to use this statistic rather than how to calculate it (Field, 2005; Zikmund et al.,
    2013).

    The Z-score, or standard score, is also integral to calculating confidence intervals. A Z-score uses standard
    deviation to compare a sample mean (�̅�𝑥) to a single data value. A Z-score of 1 indicates that a single data
    value is one standard deviation from �̅�𝑥. The Z-score will be positive if the single data value is above �̅�𝑥, and it
    will be negative if it lies below �̅�𝑥. Z-scores can be found by referring to a Z-score table or using a Z-score
    calculator. Both can be found on the internet. In the example below, a 95% confidence level equates to a Z-
    score of 1.96 or 1.96 standard deviations. As mentioned above, researchers usually use a 95% confidence
    interval, so a Z-Score of 1.96 would always be used. The other examples were included to provide an

    RCH 5301, Research Design and Methods 5

    UNIT x STUDY GUIDE
    Title

    understanding of the area under a normal curve that is included for the respective confidence intervals (see
    bell curve above) and to show the application of the appropriate Z-score based on the confidence interval
    used (Brase & Brase, 2013).

    The following will show how the standard error of the mean and Z-scores were used in the 911 call center
    scenario mentioned above.

    �̅�𝑥 – [(Z) (.4 SE)] ≤ µ ≤ �̅�𝑥 + [(Z) (.4 SE)] = Confidence Interval
    �̅�𝑥 = Sample Mean = 4.2 minutes
    Z = Z Score (Standard Deviation)
    SE = Standard Error of the Mean = .4 minutes
    µ = Population Mean

    68.27% C.I. = 3.8 minutes to 4.6 minutes

    4.2 minutes – [(1) x (.4)] = 3.8 minutes ≤ µ ≤ 4.2 minutes + [(1) x (.4)] = 4.6 minutes

    95% C.I. = 3.416 minutes to 4.984 minutes

    4.2 minutes – [(1.96) x (.4)] = 3.416 minutes ≤ µ ≤ 4.2 minutes + [(1.96) x (.4)] = 4.984 minutes

    95.45% C.I. = 3.4 minutes to 5.0 minutes

    4.2 minutes – [(2) x (.4)] = 3.4 minutes ≤ µ ≤ 4.2 minutes + [(2) x (.4)] = 5.0 minutes

    99.73% C.I. = 3.0 minutes to 5.4 minutes

    4.2 minutes – [(3) x (.4)] = 3.0 minutes ≤ µ ≤ 4.2 minutes + [(3) x (.4)] = 5.4 minutes

    Precise confidence intervals and Z-scores (standard deviations) were used in the calculations above. For
    example, a 95% confidence interval equates to a Z-score of 1.96 standard deviations. This means that +-1.96
    standard deviations from the mean represent 95% of the area under a normal curve. Compare this to the
    95.45% confidence interval that equates to a Z-score of 2 standard deviations, representing 95.45% of the
    area under a normal curve. While the Z-scores for the 95% and 95.45% confidence intervals are very close,
    researchers should use the precise Z-score (standard deviation) of 1.96, rather than 2, when calculating a
    95% confidence interval. This warning is provided to help allay any confusion since standard deviations and
    intervals under the normal curve are often simplified in usage. This simplification is referred to as the
    empirical rule, the 68-95-99.7 rule, or the three-sigma rule. For example, 1.96 standard deviations are often
    rounded to two standard deviations to represent 95% of the area under a normal curve. This is fine for quick
    forecasting, but precision is recommended for high stakes calculations (Brase & Brase, 2013; Salkind, 2009).

    The last point that is important to understand is that the confidence interval range depends on both sample
    size and the dispersion of the sample’s data values around the mean. The precision of a confidence interval
    may be increased by increasing the size of the sample. As Bell et al. (2022) comprehensively explain, there is
    an inverse relationship between sample size and sampling error. As sample size increases, the sampling
    error will decrease, and the confidence interval will become tighter and more precise. Gains in precision are
    clearly evident up to sample sizes of around 1,000 cases. After this, precision gains become much less
    noticeable. It should also be noted that it is an absolute—rather than relative—sample size that is important,
    regardless of the size of the population of interest. This means that a researcher should not be concerned
    about taking a certain percentage of the population as a sample. There is little benefit of samples larger than
    1,000, regardless of whether the population size is 1 million or 100 million.

    A larger dispersion of the data values around the sample mean will result in less confidence that the sample
    mean is a better representative of the population mean than a smaller dispersion of data values around the
    sample mean. For example, assume two samples each had a sample mean of 4.2 minutes of average wait
    times. Sample 1 has a range of values from .25 minutes to 15 minutes, while Sample 2 has a range of values
    from 4 minutes to 5 minutes. There would be more confidence that Sample 2’s mean is representative of the
    population mean due to the smaller dispersion of data values, which is reflected in a smaller standard error.

    RCH 5301, Research Design and Methods 6

    UNIT x STUDY GUIDE
    Title

    Figure 1 (Adapted from The University of Florida, n.d.)

    Central Limit Theorem

    In the discussion above about sampling error, it was noted that sampling is not perfect. If Sample 1 is from the
    population, its mean is unlikely to be an exact representative of the population mean. Additionally, if Sample 2
    is drawn from the same population, its mean would likely not represent the population mean or the Sample 1
    mean. If additional samples are drawn from the same population, it is very likely that the means from each
    sample would vary. This begs the question, how well does a single sample represent the population?

    One way to address this conundrum would be to continue to take many individual samples from the
    population. In theory, hundreds or thousands of samples would be taken from the population. For each
    sample, a sample mean (�̅�𝑥) would be calculated, resulting in a collection of many sample means.
    Remarkably, plotting the sample means in a histogram would result in a normal bell-shaped curve, called a
    sampling distribution, even if the population data is not normally distributed! This is beneficial since the
    distribution of the population is often unknown or may be known to be irregular. The central limit theorem says
    that for any population distribution at all, regardless of its shape, the sampling distribution from that population
    will be bell-shaped as long as the sample size is sufficiently large. Statisticians have determined that a
    sample size of n > 30 is sufficient for the central limit theorem to apply. If the population data is close to being
    normally distributed, then smaller sample sizes will result in normal distributions of sample means. If,
    however, the population distribution is far from normal, then larger sample sizes will be needed to ensure a
    normal distribution of sample means (Norusis, 2008).

    In addition to the sampling distribution exhibiting normality, the central limit theorem states that the average of
    the sample means would be a very close, near exact estimate of the population mean and would draw closer
    as the sample size is increased. Fortunately, as mentioned above, the standard deviation of a single sample
    can be used to estimate the standard error of the mean. This alleviates the impracticality of taking many
    samples from the same population to create a sampling distribution. A small standard error indicates that the
    sample mean is a close estimate of the population mean. Conversely, a large standard error would indicate
    that the sample mean is not a close estimate of the population mean. In short, a small standard error is good;
    a large standard error—not so much (Norusis, 2008).

    RCH 5301, Research Design and Methods 7

    UNIT x STUDY GUIDE
    Title

    In Closing

    This unit presented the basics of sampling, including populations, samples, statistical inference and
    generalization, sampling error, and confidence intervals. One simple but important takeaway from this unit
    should be that as sample size increases, sample standard deviation decreases, resulting in the sample mean
    becoming a better estimate of the population mean. Additionally, it is important to remember that sample size
    is absolute rather than relative, and after n = 1,000, the benefits of sample size begin to diminish. Therefore, a
    sample of n = 1,000 would be an optimal sample size for a population that is 1 million or 50 million.

    Unit III will explore the topics of structured interviews, surveys, and questionnaires. These are the data
    collection methods that work together with sampling. Later units will return to the idea of using inferential
    statistics for hypothesis testing.

    References

    Annenberg Learner. (2013). Confidence intervals: Against all odds—Inside statistics [Video]. Films on

    Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=111543

    Bell, E., Bryman, A., & Harley, B. (2022). Business research methods (6th ed.). Oxford University Press.

    https://online.vitalsource.com/#/books/9780192640505

    Brase, C. H., & Brase, C. P. (2013). Understanding basic statistics (6th ed.). Cengage Learning.

    Cooper, D. R., & Schindler, P. S. (2014). Business research methods (12th ed.). McGraw-Hill.

    Creswell, J. W., & Creswell, J. D. (2022). Research design: Qualitative, quantitative, and mixed methods

    approaches (6th ed.). SAGE. https://online.vitalsource.com/#/books/9781071817964

    Discovery Education. (2007). Discovering math: Advanced—Statistics and data analysis: Part 2 [Video]. Films

    on Demand.
    https://libraryresources.columbiasouthern.edu/login?auth=CAS&url=https://fod.infobase.com/PortalPl
    aylists.aspx?wID=273866&xtid=117915

    Field, A. (2005). Discovering stats using SPSS (2nd ed.). SAGE.

    Norusis, M. J. (2008). SPSS 16.0 guide to data analysis. Prentice Hall.

    The Office of Research Integrity. (n.d.) Module 4: Method of information collection – Section 2:3 [Graphic].

    https://ori.hhs.gov/node/1228/printable/print

    Salkind, N. J. (2009). Exploring research (7th ed.). Pearson Education.

    The University of Florida. (n.d.). Estimation [Graphic]. https://bolt.mph.ufl.edu/6050-6052/unit-4/module-11/

    Weaver, P. (2016, July 19). Can you use standard deviation in project management? [Chart]. Project

    Manager. https://projectmanager.com.au/can-you-use-standard-deviation-in-project-management/

    Zaman, E. (n.d.) What is the difference between population and sample? [Graphic]. BBA Lectures.

    https://www.bbalectures.com/what-is-the-difference-between-population-and-sample/

    Zikmund, W. G., Babin, B. J., Carr, J. C., & Griffin, M. (2013). Business research methods (9th ed.). Cengage

    Learning.

    **UnitIIIStudyGuide.pdf**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/unitiiistudyguide-pdf-10344473)

    – 1
    – 2
    – 3

  • [Solved] Program Evaluation: Your Point of View

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    Doctor of Health Services This week we are learning why we need to empirically test programs for different purposes. For this discussion, search online for a program that interests you. Engage in a conversation with your course community about the following: – Describe the program and why you chose …

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    Doctor of Health Services
    This week we are learning why we need to empirically test programs for different purposes. For this discussion, search online for a program that interests you. Engage in a conversation with your course community about the following:
    – Describe the program and why you chose it.
    As always, if you are relying on someone else’s ideas when presenting yours, you should reference their paper, article, etc. This includes sharing references to your fellow students’ ideas!

  • [Solved] Elevate Your Industrial Space with Premium Flooring Solutions in BD

    ✓ Verified Academic Solution Available

    Executive Solution Overview

    Elevate Your Industrial Space with Premium Flooring Solutions in BD – ## Untitleddocument7.pdf **## Untitleddocument7.pdf** Elevate Your Industrial Space with Premium Flooring Solutions in BD A well-designed floor is more than just a surface—it’s a foundation for productivity, safety, and long-term …

    Instant Solution Download

    $6.99

    Immediate access to the full model answer, formatted citations, and rubric breakdown.

    Need a Fresh Custom Paper?

    Have this question answered from scratch according to your specific instructions and deadline.

    Order on TutorsGallery →

    Assignment Prompt & Instructions

    Elevate Your Industrial Space with Premium Flooring Solutions in BD

    – ## Untitleddocument7.pdf

    **## Untitleddocument7.pdf**

    Elevate Your Industrial Space with Premium Flooring
    Solutions in BD
    A well-designed floor is more than just a surface—it’s a foundation for productivity, safety,
    and long-term performance. Whether you’re managing a factory, warehouse, or commercial
    facility, investing in the best flooring solution in BD can make a huge difference.

    That’s where Fountech comes in.

    Smart Flooring, Smarter Business

    Fountech is one of the leading providers of flooring service in Bangladesh, offering
    industrial-grade solutions that are built to withstand harsh conditions, heavy loads, and daily
    wear and tear.

    From site inspection to final polish, their team ensures every project is handled with
    precision and professionalism.

    Why Epoxy PU Flooring Is a Top Choice

    If you need a floor that’s strong, seamless, and resistant to chemicals, heat, or
    impact—Fountech’s Epoxy PU service in BD is the perfect solution.

    Epoxy gives a solid, durable finish, while polyurethane adds elasticity to prevent cracks and
    damage in high-traffic zones. It’s ideal for:

    ● Manufacturing units

    ● Pharmaceutical areas

    ● Parking zones

    ● Commercial kitchens

    ● Cold storage and more

    What Makes Fountech Stand Out?

    ● High-performance epoxy & PU materials

    ● Skilled and experienced application team

    ● Customized design based on your space

    [https://fountechbd.com](https://fountechbd.com/)

    [https://fountechbd.com](https://fountechbd.com/)

    [https://fountechbd.com](https://fountechbd.com/)

    ● Excellent after-sales support

    ● Competitive pricing without cutting corners

    Whether you're building something new or renovating an old space, Fountech ensures you
    get flooring that lasts.

    Ready to Upgrade?

    If you’re serious about quality, it’s time to explore your options. Visit Fountech’s website
    today to learn more and request a free consultation. Get the flooring that your facility truly
    deserves—with Fountech, where quality meets trust.

    [https://fountechbd.com](https://fountechbd.com/)

    – Elevate Your Industrial Space with Premium Flooring Solutions in BD
    – Smart Flooring, Smarter Business
    – Why Epoxy PU Flooring Is a Top Choice
    – What Makes Fountech Stand Out?
    – Ready to Upgrade?

    **## Untitleddocument7.pdf**

    Elevate Your Industrial Space with Premium Flooring
    Solutions in BD
    A well-designed floor is more than just a surface—it’s a foundation for productivity, safety,
    and long-term performance. Whether you’re managing a factory, warehouse, or commercial
    facility, investing in the best flooring solution in BD can make a huge difference.

    That’s where Fountech comes in.

    Smart Flooring, Smarter Business

    Fountech is one of the leading providers of flooring service in Bangladesh, offering
    industrial-grade solutions that are built to withstand harsh conditions, heavy loads, and daily
    wear and tear.

    From site inspection to final polish, their team ensures every project is handled with
    precision and professionalism.

    Why Epoxy PU Flooring Is a Top Choice

    If you need a floor that’s strong, seamless, and resistant to chemicals, heat, or
    impact—Fountech’s Epoxy PU service in BD is the perfect solution.

    Epoxy gives a solid, durable finish, while polyurethane adds elasticity to prevent cracks and
    damage in high-traffic zones. It’s ideal for:

    ● Manufacturing units

    ● Pharmaceutical areas

    ● Parking zones

    ● Commercial kitchens

    ● Cold storage and more

    What Makes Fountech Stand Out?

    ● High-performance epoxy & PU materials

    ● Skilled and experienced application team

    ● Customized design based on your space

    [https://fountechbd.com](https://fountechbd.com/)

    [https://fountechbd.com](https://fountechbd.com/)

    [https://fountechbd.com](https://fountechbd.com/)

    ● Excellent after-sales support

    ● Competitive pricing without cutting corners

    Whether you're building something new or renovating an old space, Fountech ensures you
    get flooring that lasts.

    Ready to Upgrade?

    If you’re serious about quality, it’s time to explore your options. Visit Fountech’s website
    today to learn more and request a free consultation. Get the flooring that your facility truly
    deserves—with Fountech, where quality meets trust.

    [https://fountechbd.com](https://fountechbd.com/)

    – Elevate Your Industrial Space with Premium Flooring Solutions in BD
    – Smart Flooring, Smarter Business
    – Why Epoxy PU Flooring Is a Top Choice
    – What Makes Fountech Stand Out?
    – Ready to Upgrade?