Use independent samples T$-$tests to test for differences in gender and ethnicity for the Cognitive Test, the Job$/$Person Fit test, and the Structured Interview.

The race description variable has five categories so you would need to use ANOVA to test for differences between groups on your three selection tests: Cognitive test, Job$/$Person Fit test, and the Structured Interview.

Use ANOVA to see if there a differences in race for the Cognitive test, the Job$/$Person Fit test, and the Structured Interview.

You also have a variable that references whether they were recruited through a diversity job fair. It is a dummy variable, and you can see if there are differences in the Cognitive test, the Job$/$Person Fit Test, and the Structured Interview if they were recruited through a diversity job fair or not.

Use an independent samples T$-$test to see if there are differences in the Cognitive test, the Job$/$Person Fit Test, and The Structured interview if the employee was recruited at a diversity fair.

Test for those differences and then describe what you find.

Use ANOVA to test whether there are any differences in performance based on the recruitment source. To do that you will have to convert the labels under recruitment source to numbers and then add the labels back in in the variable view of the data set. This is demonstrated in the tutorial video for this lesson. For this analysis recruitment source is the grouping variable or factor, and PerfScoreID $($their last performance appraisal rating$)$ is the dependent variable.

Use ANOVA and Regression to see if the recruitment source has any impact on the job performance score.

Next, test to see if these pre$-$employment hiring tests are related to job performance. You can do this with multiple linear regression. The dependent variable is $$PerfScoreID$($their last performance appraisal rating$).$ The independent variables are Cognitive Test, Job$/$Person Fit Test, and Structured Interview. If the variables are significant and explain a reasonable amount of variance, you have evidence that your job selection tests are $$job related$.$

Use regression to see how well the three pre$-$employment tests predict performance.

The case study also states that you can provide some job validation by evaluating the impact on turnover. In this data set you have a list of employees who have left the organization and those who are still with the organization. There is a variable labeled $$Terminated$.$ It is a dummy variable. $0$ means they are still employed and $1$ means that their employment has been terminated. You want to see if your Cognitive Test, Job$-$Person Fit Test, and Structured interview will predict turnover. If they do it provides additional job$-$related information that can be used to validate your selection tests. You can not use multiple linear regression for this test, because Multiple Linear Regression requires that the dependent variable be a continuous $($or at least ordinal$)$ variable. However, $$Terminated$$ is only a dummy variable. They either quit or did not quit. SPSS has a tool that allows you to evaluate a binary variable. It is called logistic regression. View the tutorial video about running logistic regression. Terminated is the dependent variable. Cognitive test, Job$-$person Fit Test, and Structured Interview are the covariates. Run the test and report what you learned.

Use Logistic regression to see if the cognitive test, job$-$person fit test, and the structured interview predict whether someone$$s employment has been terminated.

Submit your output files for the analyses and provide a description and explanation for what you learned.

I can provide the SPSS Data Set also, but it will not let me add it here.