# SPSS Exercises

SPSS

1. For Chapter 10’s SPSS exercises, we’ll return to the MIDUS2011 data set (Midlife in the United States Study, MIDUS Refresher, 2011–2014). We’ll run an Analysis of Variance (ANOVA) in order to look at the effect of an independent variable that is measured at the nominal level and has more than two categories.
2. We’ll run two ANOVAs in one request, with one independent variable (we’ll use marital status) and two dependent variables (measures of self-esteem and personal mastery).
1. Analyze > Compare Means > One-Way ANOVA
2. Select RA1SESTEE (self-esteem) and RA1SMASTE (personal mastery) and move into the “dependent list” box
3. Select RA1PB19 (marital status) and move into the “factor” box
4. Click Options > Descriptive
5. Click “OK” to run the test
3. Interpret the results.
1. In the Descriptives output, compare the mean levels of both dependent variables across the categories of marital status. What are the differences?
2. In the ANOVA output, examine the significance level. Were the mean differences statistically significant at the .05 level? At the .01 level? At the .001 level?
3. ANOVA tests the statistical significance of the mean differences between all the categories of the independent variable. Reexamine the Descriptives output. Does it appear that the mean levels of self-esteem and personal mastery may differ between some categories of marital status and not others?

Online Analysis

1. For Chapter 10’s SPSS exercises, we’ll return to the MIDUS2011 data set (Midlife in the United States Study, MIDUS Refresher, 2011–2014). We’ll run an Analysis of Variance (ANOVA) in order to look at the effect of an independent variable that is measured at the nominal level and has more than two categories.
2. Let’s now run an ANOVA with one independent variable (we’ll use marital status) and one dependent variable (self-esteem).
1. Analysis > Comparison of Means
2. Type RA1SESTEE (self-esteem) into the dependent variable box, and RA1PB19 (marital status) into the box labeled “row”
3. Under TABLE OPTIONS, select “Z/T-statistic” and “P-value”
4. Under OTHER OPTIONS, select “ANOVA stats”
5. Under CHART OPTIONS, select “no chart” and check the “show means” box
6. Run the table
3. Interpret the results.
1. In the Descriptives output, compare the mean levels of both dependent variables across the categories of marital status. What are the differences?
2. In the ANOVA output, examine the significance level. Were the mean differences statistically significant at the .05 level? At the .01 level? At the .001 level?
3. ANOVA tests the statistical significance of the mean differences between all the categories of the independent variable. Reexamine the Descriptives output. Does it appear that the mean levels of self-esteem and personal mastery may differ between some categories of marital status and not others?