ABSTRACT
The basic ideas associated with statistical inference were introduced in Chapter 9. We developed these ideas in the context of drawing inferences about a single population mean, and we assumed that the sample was large enough to justify appeals to the Central Limit Theorem for normal approximations. The population mean is a natural measure of centrality, but it is not the only one. Furthermore, even if we are interested in the population mean, our sample may be too small to justify the use of a large-sample normal approximation. The purpose of the next several chapters is to explore more thoroughly how statisticians draw inferences about measures of centrality.
