In This Chapter
From product advertisements to media blitzes on recent medical breakthroughs, you often run across claims made about one or more populations. For example, “We promise to deliver our packages in two days or less” or “Two recent studies show that a high-fiber diet may reduce your risk of colon cancer by 20%.” Whenever someone makes a claim (also called a null hypothesis) about a population (such as all packages, or all adults) you can test the claim by doing what statisticians call a hypothesis test.
A hypothesis test involves setting up your hypotheses (a claim and its alternative), selecting a sample (or samples), collecting data, calculating the relevant statistics, and using those statistics to decide whether the claim is true.
In this chapter, I outline the formulas used for some of the most common hypothesis tests, explain the necessary calculations, and walk you through some examples.
If you need more background information on hypothesis testing (such as setting up hypotheses, understanding test statistics, p-values, significance levels, and type-1 and type-2 errors), just flip to Chapter 14. All the general concepts of hypothesis testing are developed there. This chapter ...