Introducing Probability

Abstract

Probability is the basis of hypothesis testing and inferential statistics, so I use this concept throughout the book. (Seems like a fine time to introduce it!). Most of the time I represent probability as the proportion of area under part of a distribution. For example, the probability of a Type I error (also known as α) is the area in a tail of the standard normal distribution, or in a tail of the t distribution. It’s time to examine probability in greater detail, including random variables, permutations, and combinations. I show you some fundamentals and applications of probability, and then I focus on a couple of specific probability distributions and also tell you about some probability-related R functions.