Probability and Statistical Inference pp 64-106 | Cite as

# The Calculus of Probability

## Abstract

We recall from Section 1.3 that a probability model for an experiment has two ingredients: a sample space *S* and a probability distribution {p_{i}}. A subset of the sample space is called an event, and its probability is the sum of the probabilities of all the points it contains. In Chapter 2 we considered only cases in which all of the sample points were assumed to be equally probable. Now we return to the general case in which the p_{i}’s need not be equal. In Sections 1 and 7 we develop formulae for the probability of a union of events. Sections 2 and 3 discuss the extremely important concepts of product models and independence while Sections 4, 5, 6 deal with conditional probability models.

## Keywords

Conditional Probability Sample Space Product Rule Venn Diagram White Ball## Preview

Unable to display preview. Download preview PDF.