Modern probability provides a formal version of this intuitive idea, known as the law of large numbers. This law is remarkable because it is not assumed in the foundations of probability theory, but instead emerges out of these foundations as athcirin, Since it links theoretically derived probabilities to their actual frequency of occurrence in the real world, the law of large numbers is considered as a pillar in the history of saistical theory and has had widespread influence. Probability is a way of assigning every "eavent' a value between zearo and one, with the requirement that the event made up of all possible results (in our example, the event({1,2,3,4,5,6}) be assigned a value of one. To qualify as a probability distribution, the assignment of values must satisfy the requirement that if you look at a collection of mutually exclusive events (events that contain no common results, e.g., the events {16} {3}, and {2,4} are all mutually exclusive), the probability that at least one of the events will occur is given by the sum of the probabilities of all the individual events. This book emphasises practical instruction. It sets out to inform its readers how certain tasks should be done. The text includes inormation about the very basic area of this subject. Contents: Probability Distribution, Probability Axioms, Geometric Probability, Method of Moments, Bayesian Probability, Conditional Probability, Bayes, Theorem, Gamma Distribution, Conditional Distributions, Cauchy Distribution, Probability-generating Function.