Tag: Homework Solution

  • [Solved] PHE5020 – Week 1 Project

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    See attachment. – ## SU_PHE5020_W1_L4_G21.pdf – BiostatisticalMethods-Week1Project.docx **## SU_PHE5020_W1_L4_G21.pdf** © 2023 One-Tailed and Two-Tailed Test One-Tailed Test Alternate Indicates Greater Than Assume a= .05 and HO:µ :5: µO vs. Ha:µ> µO. This is called a one-tailed test because …

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    See attachment.

    – ## SU_PHE5020_W1_L4_G21.pdf

    – BiostatisticalMethods-Week1Project.docx

    **## SU_PHE5020_W1_L4_G21.pdf**

    © 2023

    One-Tailed and Two-Tailed Test

    One-Tailed Test

    Alternate Indicates Greater Than

    Assume a= .05 and HO:µ :5: µO vs. Ha:µ> µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too large. All of the values of a will be in the right tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    When the value of the test statistic is greater than z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the

    greater than (>) symbol.

    Confidence (C) A

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    +1.28

    +1.645

    +3.10

    Page 2 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Alternate Indicates Less Than

    Assume a= .05 and HO:µ� µO vs. Ha:µ< µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too small. All of the values of a will be in the left tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    -z"

    When the value of the test statistic is less than -z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the less

    than(<) symbol.

    Confidence (C) a

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    -1.28

    -1.645

    -3.10

    Page 3 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Two-Tailed Test

    Assume C = 95%, which means a= .05 and HO:µ= µO vs. Ha:µ ;t:. µO. This is called a two-tailed test since

    the null hypothesis will be rejected if the value of the test statistic is too small or too large. Half the value

    of a will be in each tail of the normal curve-a/2 = .025.

    When the value of the test statistic is less than -z or greater than +z, the null hypothesis will be rejected;

    otherwise, it will not be rejected-often stated as failure to reject the null hypothesis. The shaded area

    represents the area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is two tailed, or contains the not

    equal to (;t:.) symbol.

    Confidence (C) a

    90% a= .10; a/2 = .05

    95% a = .05; a/2 = .025

    99% a= .01; a/2 = .005

    Critical Value (z*)

    ± 1.645

    ± 1.96

    ± 2.576

    Page4of4 Biostatistical Methods

    ©2023 South University

    **BiostatisticalMethods-Week1Project.docx**

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    **BiostatisticalMethods-Week1Project.docx**

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    **## SU_PHE5020_W1_L4_G21.pdf**

    © 2023

    One-Tailed and Two-Tailed Test

    One-Tailed Test

    Alternate Indicates Greater Than

    Assume a= .05 and HO:µ :5: µO vs. Ha:µ> µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too large. All of the values of a will be in the right tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    When the value of the test statistic is greater than z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the

    greater than (>) symbol.

    Confidence (C) A

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    +1.28

    +1.645

    +3.10

    Page 2 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Alternate Indicates Less Than

    Assume a= .05 and HO:µ� µO vs. Ha:µ< µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too small. All of the values of a will be in the left tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    -z"

    When the value of the test statistic is less than -z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the less

    than(<) symbol.

    Confidence (C) a

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    -1.28

    -1.645

    -3.10

    Page 3 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Two-Tailed Test

    Assume C = 95%, which means a= .05 and HO:µ= µO vs. Ha:µ ;t:. µO. This is called a two-tailed test since

    the null hypothesis will be rejected if the value of the test statistic is too small or too large. Half the value

    of a will be in each tail of the normal curve-a/2 = .025.

    When the value of the test statistic is less than -z or greater than +z, the null hypothesis will be rejected;

    otherwise, it will not be rejected-often stated as failure to reject the null hypothesis. The shaded area

    represents the area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is two tailed, or contains the not

    equal to (;t:.) symbol.

    Confidence (C) a

    90% a= .10; a/2 = .05

    95% a = .05; a/2 = .025

    99% a= .01; a/2 = .005

    Critical Value (z*)

    ± 1.645

    ± 1.96

    ± 2.576

    Page4of4 Biostatistical Methods

    ©2023 South University

    **BiostatisticalMethods-Week1Project.docx**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/biostatisticalmethods-week1project-docx)

    **## SU_PHE5020_W1_L4_G21.pdf**

    © 2023

    One-Tailed and Two-Tailed Test

    One-Tailed Test

    Alternate Indicates Greater Than

    Assume a= .05 and HO:µ :5: µO vs. Ha:µ> µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too large. All of the values of a will be in the right tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    When the value of the test statistic is greater than z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the

    greater than (>) symbol.

    Confidence (C) A

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    +1.28

    +1.645

    +3.10

    Page 2 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Alternate Indicates Less Than

    Assume a= .05 and HO:µ� µO vs. Ha:µ< µO. This is called a one-tailed test because the null hypothesis

    will be rejected if the value of the test statistic is too small. All of the values of a will be in the left tail of

    the normal curve. Note the inequality in the alternative points in the direction of the rejection region.

    -z"

    When the value of the test statistic is less than -z, the null hypothesis will be rejected; otherwise, it will

    not be rejected-often stated as failure to reject the null hypothesis. The shaded area represents the

    area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is one tailed, or contains the less

    than(<) symbol.

    Confidence (C) a

    90% a= .10

    95% a=.05

    99% a= .01

    Critical Value (z*)

    -1.28

    -1.645

    -3.10

    Page 3 of4 Biostatistical Methods

    ©2023 South University

    One-Tailed and Two-Tailed Test

    Two-Tailed Test

    Assume C = 95%, which means a= .05 and HO:µ= µO vs. Ha:µ ;t:. µO. This is called a two-tailed test since

    the null hypothesis will be rejected if the value of the test statistic is too small or too large. Half the value

    of a will be in each tail of the normal curve-a/2 = .025.

    When the value of the test statistic is less than -z or greater than +z, the null hypothesis will be rejected;

    otherwise, it will not be rejected-often stated as failure to reject the null hypothesis. The shaded area

    represents the area where the null hypothesis would be rejected.

    The table below lists some common values for z* when the alternative is two tailed, or contains the not

    equal to (;t:.) symbol.

    Confidence (C) a

    90% a= .10; a/2 = .05

    95% a = .05; a/2 = .025

    99% a= .01; a/2 = .005

    Critical Value (z*)

    ± 1.645

    ± 1.96

    ± 2.576

    Page4of4 Biostatistical Methods

    ©2023 South University

    **BiostatisticalMethods-Week1Project.docx**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/biostatisticalmethods-week1project-docx)

    – 1
    – 2

  • [Solved] Policing the Future

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    3000 word APA FORMAT WITH CITED REFERENCES. TURNITIN REQUIRED PLAGIARISM REQUIRED

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    Assignment Prompt & Instructions

    3000 word
    APA FORMAT WITH CITED REFERENCES.
    TURNITIN REQUIRED PLAGIARISM REQUIRED

  • [Solved] Derivative

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    In-depth study guidance and analytical solution covering Derivative.

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    Full assignment prompt and step-by-step guidance are included in the downloadable solution file.

  • [Solved] 8

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    . – ## Paper8.docx – ## CullenandFrancisChapter1.pdf **## Paper8.docx** You must submit a 3-4 page summary of the assigned readings from this week. This is not the appropriate place to discuss whether or not you enjoyed the material, but is instead a means to assess whether or not you understood the…

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    Assignment Prompt & Instructions

    .

    – ## Paper8.docx

    – ## CullenandFrancisChapter1.pdf

    **## Paper8.docx**

    You must submit a 3-4 page summary of the assigned readings from this week. This is not the appropriate place to discuss whether or not you enjoyed the material, but is instead a means to assess whether or not you understood the material well enough to briefly summarize it. In other words, do not make your own argument in the summary papers (you will do that on your exam answers); instead, summarize the study or key arguments the author(s) are making.

    Your weekly summary paper should cover at least the three articles. Be sure to include the book "Locked in" in at least one of your summaries from the corrections modules.

    Readings:

    · Cullen, F. T., & Jonson, C. L. (2016). Correctional theory: Context and consequences. Sage Publications.

    · Chapter 1: From Theory to Policy – Evidence Based Corrections (Uploaded into Files Section of Webcourses)

    · McCorkle, R., & Crank, J. P. (1996). Meet the new boss: Institutional change and loose coupling in parole and probation. American Journal of Criminal Justice, 21, 1-25.

    · Ryan, C., & Bergin, M. (2022). Procedural justice and legitimacy in prisons: A review of extant empirical literature. Criminal Justice and Behavior, 49(2), 143-163.

    · Pfaff: Locked in (book)

    **## CullenandFrancisChapter1.pdf**

    CORRECTIONAL

    THEORY
    CONTEXT AND CONSEQUENCES

    Second Edition

    FRANCIS T. CULLEN
    University of Cincinnati

    CHERYL LERO JONSON
    Xavier University

    ISAGE

    **## CullenandFrancisChapter1.pdf**

    CORRECTIONAL

    THEORY
    CONTEXT AND CONSEQUENCES

    Second Edition

    FRANCIS T. CULLEN
    University of Cincinnati

    CHERYL LERO JONSON
    Xavier University

    ISAGE

    **## Paper8.docx**

    You must submit a 3-4 page summary of the assigned readings from this week. This is not the appropriate place to discuss whether or not you enjoyed the material, but is instead a means to assess whether or not you understood the material well enough to briefly summarize it. In other words, do not make your own argument in the summary papers (you will do that on your exam answers); instead, summarize the study or key arguments the author(s) are making.

    Your weekly summary paper should cover at least the three articles. Be sure to include the book "Locked in" in at least one of your summaries from the corrections modules.

    Readings:

    · Cullen, F. T., & Jonson, C. L. (2016). Correctional theory: Context and consequences. Sage Publications.

    · Chapter 1: From Theory to Policy – Evidence Based Corrections (Uploaded into Files Section of Webcourses)

    · McCorkle, R., & Crank, J. P. (1996). Meet the new boss: Institutional change and loose coupling in parole and probation. American Journal of Criminal Justice, 21, 1-25.

    · Ryan, C., & Bergin, M. (2022). Procedural justice and legitimacy in prisons: A review of extant empirical literature. Criminal Justice and Behavior, 49(2), 143-163.

    · Pfaff: Locked in (book)

    **## CullenandFrancisChapter1.pdf**

    CORRECTIONAL

    THEORY
    CONTEXT AND CONSEQUENCES

    Second Edition

    FRANCIS T. CULLEN
    University of Cincinnati

    CHERYL LERO JONSON
    Xavier University

    ISAGE

    **## Paper8.docx**

    You must submit a 3-4 page summary of the assigned readings from this week. This is not the appropriate place to discuss whether or not you enjoyed the material, but is instead a means to assess whether or not you understood the material well enough to briefly summarize it. In other words, do not make your own argument in the summary papers (you will do that on your exam answers); instead, summarize the study or key arguments the author(s) are making.

    Your weekly summary paper should cover at least the three articles. Be sure to include the book "Locked in" in at least one of your summaries from the corrections modules.

    Readings:

    · Cullen, F. T., & Jonson, C. L. (2016). Correctional theory: Context and consequences. Sage Publications.

    · Chapter 1: From Theory to Policy – Evidence Based Corrections (Uploaded into Files Section of Webcourses)

    · McCorkle, R., & Crank, J. P. (1996). Meet the new boss: Institutional change and loose coupling in parole and probation. American Journal of Criminal Justice, 21, 1-25.

    · Ryan, C., & Bergin, M. (2022). Procedural justice and legitimacy in prisons: A review of extant empirical literature. Criminal Justice and Behavior, 49(2), 143-163.

    · Pfaff: Locked in (book)

    **## CullenandFrancisChapter1.pdf**

    CORRECTIONAL

    THEORY
    CONTEXT AND CONSEQUENCES

    Second Edition

    FRANCIS T. CULLEN
    University of Cincinnati

    CHERYL LERO JONSON
    Xavier University

    ISAGE

    – 1
    – 2

  • [Solved] Management Theory

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    In-depth study guidance and analytical solution covering Management Theory.

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    Assignment Prompt & Instructions

    Full assignment prompt and step-by-step guidance are included in the downloadable solution file.

  • [Solved] Correlation and Chi-square

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    Executive Solution Overview

    – ## CorrelationandChi-Square.docx – classs_survey-11.sav **## CorrelationandChi-Square.docx** Part 1: Examining the relationship between two continuous variables using Pearson’s r Using the class_survey dataset and the variables Alcohol and Cigarettes, you are going to address the following resea…

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    Assignment Prompt & Instructions

    – ## CorrelationandChi-Square.docx

    – classs_survey-11.sav

    **## CorrelationandChi-Square.docx**

    Part 1: Examining the relationship between two continuous variables using Pearson’s r

    Using the class_survey dataset and the variables Alcohol and Cigarettes, you are going to address the following research questions:

    You suspect that people who drink more alcohol are also more likely to smoke cigarettes due to disinhibiting effects of alcohol use. Thus, your research question is:

    RQ1: Is there a relationship between alcohol consumption and smoking cigarettes?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for the research question.

    In SPSS: First, create a scatterplot for alcohol use and cigarette use.

    Compute Pearson’s r in SPSS for this relationship.

    Describe the scatterplots (discuss the relationship between variables).

    Then, report and discuss the bivariate correlation (i.e., significance, direction and strength) in the proper format (see examples below) and your decision regarding your hypotheses.

    You should turn in: your hypotheses, scatterplots (from spss output), written description of scatterplots and report of Pearson's r, and decision regarding hypotheses.

    Writing example for correlations:

    Pearson’s product-moment correlation was conducted to determine the relationship between hours spent studying and GPA, hours spent playing video games and GPA and hours spent studying and hours spent playing video games. Hours spent playing video games and GPA were moderately negatively correlated, r(123) = – .32, p = .041 while hours spent studying and GPA were strongly positively correlated, r(123) = .61, p = .011. Finally, hours spent playing video games and hours spent studying were moderately negatively correlated, r(123) = -.52, p = .02.

    Part 2: Examining two categorical variables using Chi-Square

    You suspect that males are more likely to report having been arrested compared to females. Thus, using the class_survey dataset and the variables Gender and Arrest, you are going to address the following research question:

    RQ1: Is having been arrested independent of gender?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for this research question.

    Conduct a chi-square test in SPSS to determine if the data fail to reject or reject the null hypothesis. Make sure to request the appropriate counts and percentages from SPSS.

    Write a paragraph describing and discussing the findings from the SPSS output. Remember to report the appropriate statistics (including any relevant percentages/counts) along with the effect size (note. follow APA format when reporting any statistics in text; make sure to properly interpret the effect size [Phi and Cramer’s V] with regard to the strength of the effect). Make sure to discuss the findings in terms of the hypotheses. Do NOT turn in your SPSS output for chi-square but make sure the proper statistics are reported in your write-up of findings.

    You should turn in: null and research hypothesis, written description of what you observed from the crosstab and chi-square test (including discussion of observed frequencies/percentages), determine decision for hypotheses, and reported effect size with mention of magnitude of the relationship.

    Examples for reporting chi-square results:

    The percentage of students who reported ever being suspended from urban schools was 25% whereas the percentage from suburban schools was 9%. Based on a chi-square test, this difference was found to be significant, χ²(1, N = 167) = 22.01, p < 0.001. Despite the significant effect, the relationship between suspension and school location was weak (Φ = .16).

    A Chi-square test of independence was calculated to determine if recidivism (a dichotomous outcome) was related to dispositional outcome (secure placement, probation, drug court). Of those receiving secure placement 38% recidivated compared to 12% receiving probation and 9% receiving drug court. These differences in recidivism across disposition were significant, χ²(2, N = 70) = 6.78, p = 0.03, V = .33.

    Please only turn in your write up for parts 1 and 2 and the scatterplots output from part 1 – that is, I do not need to see your SPSS output for the other analyses but the proper statistics should be reported.

    MAKE SURE YOUR ASSIGNMENT IS FREE FROM GRAMMATICAL ERRORS AND REPORTS STATISTICS IN THE PROPER FORMAT.

    **classs_survey-11.sav**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/classs-survey-11-sav)

    **classs_survey-11.sav**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/classs-survey-11-sav)

    **## CorrelationandChi-Square.docx**

    Part 1: Examining the relationship between two continuous variables using Pearson’s r

    Using the class_survey dataset and the variables Alcohol and Cigarettes, you are going to address the following research questions:

    You suspect that people who drink more alcohol are also more likely to smoke cigarettes due to disinhibiting effects of alcohol use. Thus, your research question is:

    RQ1: Is there a relationship between alcohol consumption and smoking cigarettes?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for the research question.

    In SPSS: First, create a scatterplot for alcohol use and cigarette use.

    Compute Pearson’s r in SPSS for this relationship.

    Describe the scatterplots (discuss the relationship between variables).

    Then, report and discuss the bivariate correlation (i.e., significance, direction and strength) in the proper format (see examples below) and your decision regarding your hypotheses.

    You should turn in: your hypotheses, scatterplots (from spss output), written description of scatterplots and report of Pearson's r, and decision regarding hypotheses.

    Writing example for correlations:

    Pearson’s product-moment correlation was conducted to determine the relationship between hours spent studying and GPA, hours spent playing video games and GPA and hours spent studying and hours spent playing video games. Hours spent playing video games and GPA were moderately negatively correlated, r(123) = – .32, p = .041 while hours spent studying and GPA were strongly positively correlated, r(123) = .61, p = .011. Finally, hours spent playing video games and hours spent studying were moderately negatively correlated, r(123) = -.52, p = .02.

    Part 2: Examining two categorical variables using Chi-Square

    You suspect that males are more likely to report having been arrested compared to females. Thus, using the class_survey dataset and the variables Gender and Arrest, you are going to address the following research question:

    RQ1: Is having been arrested independent of gender?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for this research question.

    Conduct a chi-square test in SPSS to determine if the data fail to reject or reject the null hypothesis. Make sure to request the appropriate counts and percentages from SPSS.

    Write a paragraph describing and discussing the findings from the SPSS output. Remember to report the appropriate statistics (including any relevant percentages/counts) along with the effect size (note. follow APA format when reporting any statistics in text; make sure to properly interpret the effect size [Phi and Cramer’s V] with regard to the strength of the effect). Make sure to discuss the findings in terms of the hypotheses. Do NOT turn in your SPSS output for chi-square but make sure the proper statistics are reported in your write-up of findings.

    You should turn in: null and research hypothesis, written description of what you observed from the crosstab and chi-square test (including discussion of observed frequencies/percentages), determine decision for hypotheses, and reported effect size with mention of magnitude of the relationship.

    Examples for reporting chi-square results:

    The percentage of students who reported ever being suspended from urban schools was 25% whereas the percentage from suburban schools was 9%. Based on a chi-square test, this difference was found to be significant, χ²(1, N = 167) = 22.01, p < 0.001. Despite the significant effect, the relationship between suspension and school location was weak (Φ = .16).

    A Chi-square test of independence was calculated to determine if recidivism (a dichotomous outcome) was related to dispositional outcome (secure placement, probation, drug court). Of those receiving secure placement 38% recidivated compared to 12% receiving probation and 9% receiving drug court. These differences in recidivism across disposition were significant, χ²(2, N = 70) = 6.78, p = 0.03, V = .33.

    Please only turn in your write up for parts 1 and 2 and the scatterplots output from part 1 – that is, I do not need to see your SPSS output for the other analyses but the proper statistics should be reported.

    MAKE SURE YOUR ASSIGNMENT IS FREE FROM GRAMMATICAL ERRORS AND REPORTS STATISTICS IN THE PROPER FORMAT.

    **classs_survey-11.sav**

    This file is too large to display. [View in new window](https://www.sweetstudy.com/files/classs-survey-11-sav)

    **## CorrelationandChi-Square.docx**

    Part 1: Examining the relationship between two continuous variables using Pearson’s r

    Using the class_survey dataset and the variables Alcohol and Cigarettes, you are going to address the following research questions:

    You suspect that people who drink more alcohol are also more likely to smoke cigarettes due to disinhibiting effects of alcohol use. Thus, your research question is:

    RQ1: Is there a relationship between alcohol consumption and smoking cigarettes?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for the research question.

    In SPSS: First, create a scatterplot for alcohol use and cigarette use.

    Compute Pearson’s r in SPSS for this relationship.

    Describe the scatterplots (discuss the relationship between variables).

    Then, report and discuss the bivariate correlation (i.e., significance, direction and strength) in the proper format (see examples below) and your decision regarding your hypotheses.

    You should turn in: your hypotheses, scatterplots (from spss output), written description of scatterplots and report of Pearson's r, and decision regarding hypotheses.

    Writing example for correlations:

    Pearson’s product-moment correlation was conducted to determine the relationship between hours spent studying and GPA, hours spent playing video games and GPA and hours spent studying and hours spent playing video games. Hours spent playing video games and GPA were moderately negatively correlated, r(123) = – .32, p = .041 while hours spent studying and GPA were strongly positively correlated, r(123) = .61, p = .011. Finally, hours spent playing video games and hours spent studying were moderately negatively correlated, r(123) = -.52, p = .02.

    Part 2: Examining two categorical variables using Chi-Square

    You suspect that males are more likely to report having been arrested compared to females. Thus, using the class_survey dataset and the variables Gender and Arrest, you are going to address the following research question:

    RQ1: Is having been arrested independent of gender?

    Here is what you are to do for the assignment:

    Compose a null and research hypothesis for this research question.

    Conduct a chi-square test in SPSS to determine if the data fail to reject or reject the null hypothesis. Make sure to request the appropriate counts and percentages from SPSS.

    Write a paragraph describing and discussing the findings from the SPSS output. Remember to report the appropriate statistics (including any relevant percentages/counts) along with the effect size (note. follow APA format when reporting any statistics in text; make sure to properly interpret the effect size [Phi and Cramer’s V] with regard to the strength of the effect). Make sure to discuss the findings in terms of the hypotheses. Do NOT turn in your SPSS output for chi-square but make sure the proper statistics are reported in your write-up of findings.

    You should turn in: null and research hypothesis, written description of what you observed from the crosstab and chi-square test (including discussion of observed frequencies/percentages), determine decision for hypotheses, and reported effect size with mention of magnitude of the relationship.

    Examples for reporting chi-square results:

    The percentage of students who reported ever being suspended from urban schools was 25% whereas the percentage from suburban schools was 9%. Based on a chi-square test, this difference was found to be significant, χ²(1, N = 167) = 22.01, p < 0.001. Despite the significant effect, the relationship between suspension and school location was weak (Φ = .16).

    A Chi-square test of independence was calculated to determine if recidivism (a dichotomous outcome) was related to dispositional outcome (secure placement, probation, drug court). Of those receiving secure placement 38% recidivated compared to 12% receiving probation and 9% receiving drug court. These differences in recidivism across disposition were significant, χ²(2, N = 70) = 6.78, p = 0.03, V = .33.

    Please only turn in your write up for parts 1 and 2 and the scatterplots output from part 1 – that is, I do not need to see your SPSS output for the other analyses but the proper statistics should be reported.

    MAKE SURE YOUR ASSIGNMENT IS FREE FROM GRAMMATICAL ERRORS AND REPORTS STATISTICS IN THE PROPER FORMAT.

    **classs_survey-11.sav**

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  • [Solved] Case 2

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    – ## Case2.docx **## Case2.docx** Case 2 O.R. is a 42-year-old female patient that was evaluated by you at the office today. After your evaluation you concluded that she has Toxic Shock Syndrome. · Discuss and described the pathophysiology and symptomology/clinical manifestations of TSS. · Discuss t…

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    – ## Case2.docx

    **## Case2.docx**

    Case 2

    O.R. is a 42-year-old female patient that was evaluated by you at the office today. After your evaluation you concluded that she has Toxic Shock Syndrome.

    · Discuss and described the pathophysiology and symptomology/clinical manifestations of TSS.

    · Discuss three differential diagnoses for AUB with ICD 10 numbers for each.

    · Discuss patient education.

    · Develop the management plan (pharmacological and nonpharmacological).

    ·
    **An effective health assessment incorporates not only physiological parameters; please suggest other parameters that should be considered and included on health assessments to reach maximal health potential on individuals.**

    ·
    **Name the different family developmental stages and give examples of each one.**

    ·
    **Describe family structure and function and the relationship with health care.**

    Your initial post should be at least 500 words, formatted and cited in current APA style with support from at least 2 academic sources.

    **## Case2.docx**

    Case 2

    O.R. is a 42-year-old female patient that was evaluated by you at the office today. After your evaluation you concluded that she has Toxic Shock Syndrome.

    · Discuss and described the pathophysiology and symptomology/clinical manifestations of TSS.

    · Discuss three differential diagnoses for AUB with ICD 10 numbers for each.

    · Discuss patient education.

    · Develop the management plan (pharmacological and nonpharmacological).

    ·
    **An effective health assessment incorporates not only physiological parameters; please suggest other parameters that should be considered and included on health assessments to reach maximal health potential on individuals.**

    ·
    **Name the different family developmental stages and give examples of each one.**

    ·
    **Describe family structure and function and the relationship with health care.**

    Your initial post should be at least 500 words, formatted and cited in current APA style with support from at least 2 academic sources.

  • [Solved] Kim Woods Only

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    IND-299 Week 3 Assignment Only HUM-102 Week 3 Assignment Only **Will pay full bid for direct submission** WEEKLY WORK AVAILABLE

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    IND-299 Week 3 Assignment Only
    HUM-102 Week 3 Assignment Only
    **Will pay full bid for direct submission**
    WEEKLY WORK AVAILABLE

  • [Solved] eClinialWorks

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    – ## DescribeeClinicalWorks.docx **## DescribeeClinicalWorks.docx** Describe eClinicalWorks (ECW) the electronic health records (EHR) that is used in my clinical practice A. What are the Pros and cons you have found. B. Is E-prescription incorporated on the EMH? C. Does it have adaptive learning? D….

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    – ## DescribeeClinicalWorks.docx

    **## DescribeeClinicalWorks.docx**

    Describe eClinicalWorks (ECW) the electronic health records (EHR) that is used in my clinical practice

    A. What are the Pros and cons you have found.

    B. Is E-prescription incorporated on the EMH?

    C. Does it have adaptive learning?

    D. Does it have Incorporated patient doorway?

    E. Is there Flexibility with the absence of internet connectivity?

    F. Does it have effective documentation and Image management capability.

    Support and share your personal experience so all of us can learn.

    **Submission Instructions:**

    · Your initial post should be at least 500 words, formatted and cited in current APA style with support from at least 2 academic sources.

    **## DescribeeClinicalWorks.docx**

    Describe eClinicalWorks (ECW) the electronic health records (EHR) that is used in my clinical practice

    A. What are the Pros and cons you have found.

    B. Is E-prescription incorporated on the EMH?

    C. Does it have adaptive learning?

    D. Does it have Incorporated patient doorway?

    E. Is there Flexibility with the absence of internet connectivity?

    F. Does it have effective documentation and Image management capability.

    Support and share your personal experience so all of us can learn.

    **Submission Instructions:**

    · Your initial post should be at least 500 words, formatted and cited in current APA style with support from at least 2 academic sources.

  • [Solved] Can you assist ?

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