ABSTRACT
This chapter examines the fundamental principles of Bayesian probability theory. In general, this is a methodology used to try to clarify the relationship between theory and evidence. The classical approach to probability theory describes the probability of an event occurring in terms of the proportion of times than an event can theoretically be expected to occur in terms of the total possible numbers of outcomes. Thus, A third class of information is based on a combination of observation and information supplied by theory and is generally classed as hypothetical-observational data. Although probability theory is critical for effective data analysis, deductive logic seeks to move from a cause to determine probable effects or outcomes. In the 1700s, the Reverend Thomas Bayes postulated a theory that it was possible, given the outcome of the second event in a sequence of two events, to determine the probability of various possibilities for the first event.
