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Quantitative Methods: T Tests and ANOVA

Quantitative Methods: T Tests and ANOVA

Quantitative Methods: T Tests and ANOVA

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.

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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. Quantitative Methods: T Tests and ANOVA

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

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    Week_5_tTest_ExercisesandANNOVArevised2017.doc

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    SPSS Exercise Week 5: Assignment 3

    This assignment has 2 different assigments: t Test and ANOVA. Work through each and make sure to answer all questions. Please read the directions carefully. This form should be submitted in the correct submission entry. Each document (word) should be saved with your last name and first initial in the title. Please email your instructor with any questions.

    Week 5 Independent t Test Exercises

    The hypothesis being tested is: Women who are working will have a lower level of depression as compared with women who are not working. Quantitative Methods: T Tests and ANOVA

    Using Polit2SetC SPSS data set, which contains a number of mental health variables, determine whether the above hypothesis is true.

    Follow these steps when using SPSS:

    Open Polit2SetC data set.

    Click on Analyze, then click on Compare Means, then Independent Sample T-test.

    Move the Dependent Variable (CES_D Score “cesd”) in the area labeled “Test Variable.”

    Move the Independent Variable (Currently Employed “worknow”) into the area labeled “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 on Continue and then click on OK.

    Part I

    Assignment: Through analysis of the data and use of the questions below your findings from this t-test.

    How many women were employed versus not employed in the sample?

    What is the total sample size?

    What are the mean and (SD) CES-D scores for each group?

    Interpret the Levene’s statistic. Write a few sentences to answer this question. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)

    What is the value of the t-statistic, number of degrees of freedom and the p-value?

    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 data set, determine whether the above hypothesis is true.

    Follow these steps when using SPSS:

    Open Polit2SetC data set.

    Click on Analyze, then click on Compare Means, then Paired Samples T-test.

    First click on CES-D Score (cesd) and move it into the box labeled “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).

    Click on Continue and then click on OKAssignment: Through analysis of the data and use of the questions to summarizing your findings from this t-test.

    What is the total sample size?

    What are the mean and (SD) CES-D scores at wave 1 and wave 2?

    What is the mean difference between the two time periods?

    What is the value of the t-statistic, number of degrees of freedom and the p-value(sig)?

    Does the data support the hypothesis? Why or why not?

    Part III

    Using Polit2SetC data set, 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:

    Open Polit2SetC data set.

    Click on Analyze, then click on Compare Means, then Independent Sample T-test.

    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 labeled “Test Variable.”

    Move the Independent Variable (Educational Attainment [educatn]) into the area labeled “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.

    Click on Continue and then click on OK.

    Assignment: Create a table to present your results, use the table 6.3 in Chapter 6 in your book as a model. Write one or two paragraphs explaining your results below the table.

    Week 5 ANOVA Exercises

    Research Question: Is there a difference in the overall satisfaction of women based on the number of housing problems (no problems, 1 problem, 2 or more problems)?

    Using Polit2SetA data set, run an ANOVA using Overall Satisfaction, Material Well-Being (satovrl) as the dependent variable and Housing Problems (hprobgrp) (this is the last variable in the data set) as the independent variable.

    Follow these steps when using SPSS:

    Open Polit2SetA data set.

    Click on Analyze, then click on Compare Means, then One-way ANOVA.

    Move the Dependent Variable (Overall Satisfaction “satovrl”) in the box labeled “Dependent List” by clicking the arrow button. The dependent variable is a continuous variable.

    Move the Independent Variable (Housing Problems “hprobgrp”) into the box labeled “Factor.” The hprobgrp is a categorical variable coded as (1= no hoursing problem, 2=one housing problem, 3=two or more housing problems).

    Click on the Options button (right side of box) and click on Descriptives and Homogeneity of Variance and then click on Continue.

    Click on Post Hoc (right side of box). Click on Tukey and then click on Continue.

    Click on OK.

    Assignment: Through analysis of the data and use of the questions below:

    What is the total sample size?

    How many women were in each of the different hprobgrp groups?

    What are the mean and (SD) overall satisfaction scores for each group?

    Interpret the Levene’s statistic. Write a few sentences to answer this question. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)

    What is the value of the F-statistic, number of degrees of freedom and the p-value?

    Is there a significant difference in the overall satisfaction level of women in each of the hprobgrp groups?

    Interpret the post hoc test. When interpreting the post hoc test indicate the mean and standard deviation for each group and indicate which group was signifantly higher or lower from the other. If there is no difference between two groups indicate that as well.

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    Week_5_tTest_Exercises2.doc

    Week 5 Independent t Test 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. Quantitative Methods: T Tests and ANOVA

    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:

    Open Polit2SetC dataset.

    Click Analyze then click Compare Means, then Independent Sample T-test.

    Move the Dependent Variable (CES_D Score “cesd”) in the area labelled Test Variable.

    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.

    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.

    How many women were employed versus not employed in the sample?

    What is the total sample size?

    What are the mean (SD) CES-D scores for each group?

    Interpret the Levene’s statistic. (Hint: Is the assumption of homogeneity of variance met? Are equal variances assumed or not assumed?)

    What is the value of the t-statistic, number of degrees of freedom and the p-value?

    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:

    Open Polit2SetC dataset.

    Click Analyze then click Compare Means, then Paired Samples T-test.

    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).

    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.

    What is the total sample size?

    What are the mean (SD) CES-D scores at wave 1 and wave 2?

    What is the mean difference between the two time periods?

    What is the value of the t-statistic, number of degrees of freedom and the p-value(sig)?

    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). Quantitative Methods: T Tests and ANOVA

    Follow these steps when using SPSS:

    Open Polit2SetC dataset.

    Click Analyze then click Compare Means, then Independent Sample T-test.

    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.

    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.

    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.

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    WK5Polit2SetA1.sav