Chapter 17

IN THIS CHAPTER

**Defining probability**

**Working with probability**

**Dealing with random variables and their distributions**

**Focusing on the binomial distribution**

**Learning probability-related R functions**

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.

Most of us have an intuitive ...

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