ABSTRACT
In the previous two chapters, we focused on the tests and condence intervals for means and standard deviations. In this chapter, we extend the discussion of testing of distributions and means.
One of the fundamental bases in any statistical analysis of measurements is our ability to describe the data within the context of a model or probability distribution. These models are utilized primarily to describe the shape and area of a given process, so that probabilities may be associated with questions concerning the occurrence of scores of values in the distribution. Common probability distributions for discrete random variables include the binomial and Poisson distributions. Probability distributions employed to describe continuous random variables include the normal, exponential, Weibull, gamma, and lognormal.
