In this chapter, we took a detour through probability land. You learned some basic laws of probability, sample spaces, and conditional independence. You also learned how to derive Bayes' Theorem and learned that it provides the recipe to update hypotheses in the light of new evidence.
We also touched on the two primary interpretations of probability. In future chapters, we will be employing techniques from both these approaches.
We concluded with an introduction to sampling from distributions and used two—binomial and normal—distributions to answer interesting non-trivial questions about probability.
This chapter laid the important foundation that supports confirmatory data analysis. Making and checking inferences based on data is all about probability and, at this point, we know enough to move on to have a great time testing hypotheses with data!