ABSTRACT
This chapter introduces the probability distributions which are relevant for the theory of quality control, among them the Bernoulli distribution, the Poisson distribution, the normal distribution, the binomial distribution and the hypergeometric distribution. The Poisson distribution is an appropriate stochastic model for many random processes. It is generally used to describe relatively rare events. The simplest, in quality control, however, the rarest, form of a continuous distribution is the rectangular distribution. It is the continuous analogue of the discrete uniform distribution and is usually called the continuous uniform distribution. A function parameter specifies a distribution and occurs explicitly in the distribution function, massfunction or density. A functional parameter is a quantity that depends on the underlying distribution and its function parameters. The chapter presents the idea of statistical testing and will cover in depth the risks and errors involved in testing hypotheses. It illustrates the terms “power function” and “operating characteristic function”, which are of central importance in testing theory.
