Chapter 8 - Random Sampling: Planning Ahead for Data Gathering

Abstract

This chapter focuses on random sampling. Sampling is used to learn about a system that is too large and costly to study in its entirety. A population is the collection of units (people, objects, or whatever). A sample is a smaller collection of units selected from the population and is representative if each characteristic (and combination of characteristics) arises the same percent of the time in the sample as in the population. A sample that is not representative in an important way is said to show bias. A random sample or simple random sample is selected such that (1) each population unit has an equal probability of being chosen and (2) units are chosen independently, without regard to one another. Concepts of random sample, selecting a random sample, and sampling by shuffling the population are presented in the chapter. It describes thecorrection for small populations and the standard error of the binomial proportion. The sampling distribution and the central limit theorem are explained in the chapter.