Sampling Distributions

Abstract

Statistical inference is a process of drawing conclusions about a population value (a parameter) based on a value computed from a random sample (a statistic). Every possible sample drawn from the population may yield a different statistic, however. The sampling distribution is the distribution of all possible values of a particular statistic, each with an associated probability. In this chapter, we use SPSS to simulate drawing random samples from a population, computing a particular statistic, and constructing its sampling distribution. In particular, we simulate the sampling distribution of a single observation drawn from a standard normal population distribution, the distribution of the sum of two observations drawn at random, and the distribution of the mean of 100 observations drawn from a population.