The Foundations of Inferential Statistics: Samples and Sampling

We began this unit by discussing probability and the normal distribution. In this unit, you learned about probability and why this topic is critical to your understanding of inferential statistics. We then discussed the normal distribution and one particular type of normal distribution, the standard normal distribution. The standard normal distribution is a distribution in which the mean equals zero, and the standard deviation equals one. You can use the standard normal distribution and the standard normal table to gather details about normally distributed populations. Finally, you learned about Z scores and how to transform raw scores into Z scores and Z scores into raw scores.

In this module, we will review probability samples and learn about sampling distributions. At first glance, a sampling distribution may appear similar to a normal distribution. It is bell-shaped, symmetrical, and has more frequently occurring cases on the ends. However, the sampling distribution is very different from a normal distribution.