Estimation

Abstract

In Chapter 9 we outlined the essential ideas of statistical inference. We noted that whenever a sample is taken and that sample is used to make inferences about the value of the parameters of the population from which the sample was taken, those inferences will be subject to sampling error (because no sample is a completely accurate description of the population in question). Measuring the likely size of this sampling error requires information on the sampling distribution of the sample statistic being used and in Chapter 10 we examined the sampling distribution of three commonly used sample statistics, the sample mean $$, the sample variance s², and the sample proportion p.