The probabilities in a probability model must sum to 1. When the outcomes of an experiment are all equally likely, we can find the probability of an event by dividing the number of outcomes in event by the total number of outcomes in sample space for the experiment. By reviewing the basic facts and formulae studied earlier in Class 11, we shall implement those formulas again in this chapter along with the advance concepts mentioned, i.e. conditional probability, properties of conditional probability, multiplication theorem on probability, multiplication rule of probability for more than two events, independent events, Baye’s theorem, the partition of a sample space, a theorem on total probability, random variables and its probability distributions, the probability distribution of random variable, mean of random variable, variance of random variable, Bernoulli trials and binomial distribution with various examples. We have compiled here the solutions to exercises from this chapter, which have explained the concept thoroughly.