Statistical Concepts

Abstract

A statistical distribution is a mathematical function that defines how outcomes of an experimental trial occur randomly in a probable way. The outcomes are called random variables, and their admissible region lies in a specified sample space that is associated with each individual distribution. The statistical distributions are mostly of two type: continuous and discrete. The continuous probability distributions apply when the random variable can fall anywhere between two limits, such as the amount of rain-water that accumulates in a five-gallon container after a rainfall. The discrete probability distribution pertains when the outcomes of the experiment are specific values, like the number of dots that appear on a roll of two dice. The distributions may also be classified as univariate or multivariate. The univariate is when the distribution has only one random variable; multivariate is when two or more random variables are associated with the distribution. The statistical distributions in this book pertain to the commonly used univariate continuous and discrete probability distributions, and to the most frequently applied bivariate continuous statistical distributions, where bivariate distributions have two jointly related random variables.