This document provides an overview of key concepts in probability models, including: 1. A probability model consists of a sample space (the set of all possible outcomes) and probabilities assigned to each outcome. Common examples are coin tosses and dice rolls. 2. Events are subsets of outcomes from the sample space. The probability of an event, written P(A), is the chance it occurs. 3. For mutually exclusive events like getting a sum of 5 or 6 on dice, the total probability is the sum of the individual probabilities. Basic rules of probability include that all probabilities must sum to 1 and the probability of an event's complement is 1 minus the original probability.