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PART IV

Correlation, Regression, and Nonparametric Statistical Tests

Chapter 13 The Pearson Correlation Coefficient

Chapter 14 Simple and Multiple Linear Regression

Chapter 15 Nonparametric Statistical Tests: Chi-Square

Chapter 16 Selecting the Right Statistical Test

Congratulations! This is the final section of the book and you are just four chapters away from completing your first statistics course. Up to this point, we have discussed a group of hypothesis tests called difference tests. These tests, which include the various t tests and ANOVAs, allow researchers to determine whether two or more populations differ on an outcome variable.

Now, the final chapters will introduce you to a second group of hypothesis tests called relationship tests. These tests allow researchers to analyze whether an association, or correlation, exists between two or more variables.

Chapter 13 introduces the Pearson correlation coefficient, or Pearson r, a test used to measure the strength of a relationship between two interval/ratio variables. Chapter 14 then takes the Pearson r and uses it in something called linear regression to predict a case’s score on the outcome variable from its score on the explanatory variable. Chapter 15 covers nonparametric tests, tests that can be used with ordinal- or nominal-level outcome data.

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By the end of Chapter 15, this book will have put more than a dozen statistical tests into your statistical toolbox and taught you the proper use of each one. But, students often stumble when, facing a statistical task on their own, they have to reach into their toolbox and pick the right test. That’s where Chapter 16 on selecting the correct test comes in. After completing this final chapter, you should feel confident that when you open your toolbox, you will choose the right test.