ABSTRACT
This chapter describes the characteristics of several different kinds of distributions such as random variable distributions, continuous distributions, normal distribution, discrete distributions and chi-squared distribution. It is a fortunate thing that most processes that have a stochastic element can be described in terms of just a few different kinds of random variable distributions. The values of the gamma distribution must in general be calculated numerically, due to the difficulty of evaluating its defining integral in closed form. The Bayesian statement of conditional probability holds that: The form of the exponential distribution is monotonic. A number of distributions have qualities that make them especially well-suited for particular applications. The normal distribution is perhaps the most important of the continuous distributions in statistics. An important special case of the normal distribution is the standard normal. The use of continuous and discrete probability distributions provides a convenient and in most cases mathematically tractable way to describe real systems.
