ABSTRACT
This chapter explains the concept of probability that has served as the cornerstone of inferential statistics. It defines probability and explains what objective and subjective probabilities are. The chapter measures probability, using the counting techniques. It explains the rules for combining probabilities and presents the Bayes' theorem and how it is used. The chapter explains what a probability distribution is and how to compute the binomial distribution probabilities. It utilizes the table of areas for a standard normal curve to determine probabilities of a normal distribution. The chapter defines probability as a measure of the degrees of belief one has in a particular outcome of an event. The probability of an event that is certain to occur is one, and the probability of an event that will not occur is zero. Probability computations basically follow either addition or multiplication rules. The probability of occurrence of one event given that another related event has occurred is called a conditional probability.
