This document defines key probability concepts and summarizes different approaches to assigning probabilities: 1. It defines classical, empirical, and subjective probability, and explains concepts like experiments, events, outcomes, and rules for computing probabilities. 2. Empirical probability is based on observed frequencies over many trials, while subjective probability is used when past data is limited. 3. Tools for organizing and calculating probabilities are discussed, including tree diagrams, contingency tables, conditional probability, Bayes' theorem, and counting rules.

1. A Survey of Probability Concepts Chapter 5

4. Probability Examples

6. Experiments, Events and Outcomes

15. Summary of Types of Probability

33. Bayes Theorem - Example

34. Bayes Theorem – Example (cont.)

35. Bayes Theorem – Example (cont.)

36. Bayes Theorem – Example (cont.)

38. Bayes Theorem – Example (cont.)

42. Counting Rules – Multiplication: Example

47. End of Chapter 5