ABSTRACT
In previous chapters, we learned about various statistical distributions that can be studied using the Monte Carlo technique. In this chapter, we will learn that there are many different sampling distributions, each providing an estimate of its corresponding population parameter. In subsequent chapters, we will learn how the sampling distributions of various statistics are used to make inferences and test hypotheses. The sampling distribution is a frequency distribution of a statistic created by taking repeated samples of a given size from a population. Consequently, we can create sampling distributions of the mean, variance, standard deviation, range, or median, as well as many other sample statistics, with each providing a sample estimate of a corresponding population parameter.
