In Chapter 8, I introduced hypothesis testing and illustrated how to apply the concepts when testing a hypothesis about a population proportion. Throughout the rest of this book, we discuss hypothesis testing at length, starting with this chapter. As you progress through this chapter and the rest of the book, you will notice variations in the specifics of hypothesis testing. However, all hypothesis tests described in this book are governed by the same principle of confirmation through falsification and the use of a p-value for deciding between two statistical hypotheses (the null and the alternative). The procedures in this chapter focus entirely on testing hypotheses that can be phrased statistically in terms of a single mean. The wide majority of research hypotheses tested by communication researchers focus on differences between groups or the relationship between two or more variables rather information about a single measure such as a mean computed in a single sample. However, because of its simplicity, we focus first on this simple test because it serves as a good introduction to the specifics of hypothesis testing, and mastering these procedures will give you valuable practice for the more advanced problems later in this book. Having said this, one of the tests in this chapter is used quite frequently in communication science in a special form. This test focuses on a comparison of means when the data come from a “matched pairs” research design. So there is some applied value in mastering the material in this chapter as well.