ABSTRACT
This chapter focuses on building another probability distribution, this time a distribution of mean differences and discusses the conducting and interpreting the difference-of-means test (t-test). It shows that how a t- test really works and discusses conducting and interpreting an analysis of variance (ANOVA). The chapter also shows how ANOVA really works and examines the similarities and differences between ANOVA and the chi-square test. It suggests that how researchers used t-tests to study gender overcompensation and argues how a researcher used t-tests in her experiment on race relations. The chapter also suggests how researchers used ANOVA to study the effects of pets at work. It applies inferential ideas to situations where we have more than one sample mean and are seeking to make claims about more than one population mean. The chapter utilizes two additional inferential techniques: the difference-of-means test (or the t-test for short) and the analysis of variance (or ANOVA for short).
