- Produce a histogram and a boxplot for the “years married prior to separation” (mar) variable.
- How many outliers are suggested by the histogram?
- How many outliers are suggested by the boxplot?
- Use the z-score method to identify outliers. Using the ID variable, please indicate which cases are identified as outliers using the z-score method?
- Run a independent samples t-test using gender as the predictor and years married prior to separation as the dependent variable.
- State the null and alternative hypotheses.
- Using one sentence, report the t-test results

- Was the t-test significant? Interpret the results in light of the significance value.

- Did the t-test suggest small, medium, or large differences between gender of the individuals and years married prior to separation? (Hint: use G*Power to calculate Cohen’s d, and then use the rules of thumb in the lecture notes).
- Now, take out the outliers detected using the z-score method (i.e., delete them from the dataset). Now run the t-test again. Was there any change in either the interpretation of the significance probability value or the effect

** W**hat are the effects of marital status (__excluding the widowed group__) on life satisfaction?

- State the independent and dependent
- State the null and alternate
- Run the appropriate analysis using SPSS (Hint: Use the General Linear Models

and Univariate Procedure. Select Estimates of Effect Size under the Options tab).

- What are the mean and standard deviation for each of the levels of the IV?
- Report the appropriate F statistic, degrees of freedom, p value, and eta squared (η2).
- What is your decision regarding the null hypothesis (i.e., did you reject or fail to reject the null)? Explain your decision (1 sentence)
- What is the effect size for this analysis? (i.e., the eta squared). Was the effect size small, medium, or large?
- Suppose you wanted to conduct a new study that includes marital status and life satisfaction. Based on a power analysis using G*Power, what is the minimum sample size required for running the study based on power of .80.

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