ABSTRACT
One of the most important concepts in probability is the idea of a probability distribution. This chapter discusses the discrete probability distribution which is very important tool in probability and statistics, and considers two valuable distributions which frequently arise in practice. The distribution has a wide range of practical applications, ranging from sampling inspection to the failure of rocket engines. These probabilities define a discrete probability distribution customarily called the binomial distribution. A discrete distribution can be represented pictorially by a bar chart. The idea of an expected value is extremely useful when calculating the theoretical variance, and hence the theoretical standard deviation, of a probability distribution. Another important discrete distribution is the Poisson distribution, which is named after a French mathematician. The Poisson distribution has two main applications; firstly for describing the number of 'accidents' which occur in a certain time interval, and secondly as a useful approximation to the binomial distribution when the binomial parameter is small.
