This document provides instructions for analyzing data using t-tests and ANOVA. It includes 3 parts: 1) An independent samples t-test to compare depression scores between employed and unemployed women, finding support for lower depression among employed women. 2) A paired samples t-test to compare depression scores over time, finding no significant difference. 3) Independent t-tests comparing education levels on depression, physical, and mental health scores, with results presented in a table. The document guides the user through performing these analyses in SPSS and interpreting the results.

1. T Tests And ANOVA Discussion 3
T Tests And ANOVA Discussion 3T Tests And ANOVA Discussion 3To 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 IThe 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. T Tests And ANOVA Discussion 3Follow 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 IIHypothesis: 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

2. (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 IIIUsing
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. REFERENCESGray, 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 DifferenceORDER NOW FOR CUSTOMIZED, PLAGIARISM-FREE PAPERST Tests And
ANOVA Discussion 3