T-test and ANOVA Exercises

The hypothesis being tested is: Women who are working will have a lower level of depression as compared to women who are not working.
Using Polit2SetC SPSS dataset, which contains a number of mental health variables, determine if the above hypothesis is true.
Follow these steps when using SPSS:
1.    Open Polit2SetC dataset.
2.    Click Analyze then click Compare Means, then Independent Sample T-test.
3.    Move the Dependent Variable (CES_D Score “cesd”) in the area labelled Test Variable.
4.    Move the Independent Variable (Currently Employed “worknow”) into the area labelled Grouping Variable. The worknow variable is coded as (0= those women who do not work and 1= those women who are working).  Click on Define Groups in group 1 box type 0 and in group 2 box type 1. Click Continue.
5.    Click continue and then click OK.
Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
1.    How many women were employed versus not employed in the sample?
2.    What is the total sample size?
3.    What are the mean (SD) CES-D scores for each group?
4.    Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)
5.    What is the value of the t-statistic, number of degrees of freedom and the p-value?
6.    Does the data support the hypothesis? Why or why not?
Part II
Hypothesis: Women who reported depression scores in wave 1 and wave 2 of the study did not have a significant difference in their level of depression.
Using Polit2SetC SPSS dataset, determine if the above hypothesis is true.
Follow these steps when using SPSS:
1.    Open Polit2SetC dataset.
2.    Click Analyze then click Compare Means, then Paired Samples T-test.
3.    First click on CES-D Score (cesd) and move it into the box labelled Paired Variables (in the rectangle for Pair 1 of Variable 1 and then click on CESD Score, Wave 1 (cesdwav1) and move it into the Paired Variables box (in the rectangle next to CES-D Score, pair 1, variable 2).
4.    Click continue and then click OK.

Assignment: Through analysis of the data and use of the questions below write one to two paragraphs summarizing your findings from this t-test.
1.    What is the total sample size?
2.    What are the mean (SD) CES-D scores at wave 1 and wave 2?
3.    What is the mean difference between the two time periods?
4.    What is the value of the t-statistic, number of degrees of freedom and the p-value(sig)?
5.    Does the data support the hypothesis? Why or why not?
Part III
Using Polit2SetC dataset, run independent groups t-tests for three outcomes. The outcome variables are CES-D Score (cesd), SF12: Physical Health Component Score, standardized (sf12phys) and SF12: Mental Health Component Score, standardized (sf12ment).
Follow these steps when using SPSS:
1.    Open Polit2SetC dataset.
2.    Click Analyze then click Compare Means, then Independent Sample T-test.
3.    Move the Dependent Variables (CES_D Score “cesd”, SF12: Physical Health Component Score, standardized (sf12phys), and SF12: Mental Health Component Score, standardized (sf12ment) ) in the area labelled Test Variable.
4.    Move the Independent Variable (Educational Attainment “educatn”) into the area labelled Grouping Variable. The educatn variable is coded as (1= no high school credential and 2=diploma or GED).  Click on Define Groups in group 1 box type 1 and in group 2 box type 2. Click Continue.
5.    Click continue and then click OK.
Assignment: Create a table to present your results, use the table 6.3 in Chapter 6 as a model.  Write one or two paragraphs explaining your results.

Week 5 Learning Resources

This page contains the Learning Resources for this week. Be sure to scroll down the page to see all of this week’s assigned Learning Resources.
Required Resources
Note: To access this week’s required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.
Readings
•    Kovner, A. R., &Knickman, J. R. (Eds.). (2011). Health care delivery in the United States (Laureate Education, Inc., custom ed.). New York, NY: Springer Publishing.
o    Chapter 7, “Health and Behavior” (pp. 125–129)

This chapter discusses the role of behavior on health and describes behavioral risk factors and potential community-based interventions.
Backer, E. L., Geske, J. A., McIlvain, H. E., Dodendorf, D. M., &Minier, W. C. (2005). Improving female preventive health care delivery through practice change: An Every Woman Matters study. Journal of the American Board of Family Practice, 18(5), 401–408.
Retrieved from the Walden Library databases.

This article informs the Assignment as an example of a health program that was not successful. You will conduct additional research on this topic to determine current advocacy programs that have been more effective.
Hancock, C., & Cooper, K. (2011). A global initiative to tackle chronic disease by changing lifestyles.Primary Health Care, 21(4), 24–26.
Retrieved from the Walden Library databases.

This article details the efforts of the C3 Collaborating for Health charity. In particular, C3 focuses on minimizing the risk factors of poor dieting, smoking, and low physical activity.
Schwartz, S. M., Ireland, C., Strecher, V., Nakao, D., Wang, C., & Juarez, D. (2010). The economic value of a wellness and disease prevention program. Population Health Management, 13(6), 309–317.
Retrieved from the Walden Library databases.

The authors of this article detail a study that sought to determine the economic consequences of a disease prevention program conducted by the Hawaii Medical Service Association.
Tengland, P. (2010). Health promotion and disease prevention: Logically different conceptions? Health Care Analysis, 18(4), 323–341.
Retrieved from the Walden Library databases.

This article investigates the differences and causal connections between health promotion and disease prevention.

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