ABSTRACT
The area of statistical inference may be divided into two broad categories: estimation and hypothesis testing. In particular, these two categories pertain to the estimation of parameters or testing hypotheses involving the parameters of a given distribution that models a corresponding underlying population. The parameters that are involved in a distribution are, in general, unknown. Consequently, it is of interest and importance to be able to obtain information regarding them. This information is obtained in part by estimating them and involves the calculation of numerical values from sample data that estimate the true values of the corresponding population parameters. These numerical values are called estimates of the actual population parameters. In this chapter we develop statistical procedures for estimating the parameters of various populations. The corresponding ideas concerned with hypothesis testing are the subject of Chapter 7.
