ABSTRACT
In the preceding chapter, we examined several theoretical probability distributions, such as the binomial distribution and the normal distribution. In all cases, the relevant population parameters were assumed to be known; this allowed us to describe the distributions completely and to calculate the probabilities associated with various outcomes. In most practical applications, however, we are not given the values of these parameters. Instead, we must attempt to describe or estimate some characteristic of a population— such as its mean or standard deviation—using the information contained in a sample of observations. The process of drawing conclusions about an entire population based on the information in a sample is known as statistical inference.
