# Book: Applied Probability (Pfeiffer)

- Page ID
- 10810

This is a "first course" in the sense that it presumes no previous course in probability. The mathematical prerequisites are ordinary calculus and the elements of matrix algebra. A few standard series and integrals are used, and double integrals are evaluated as iterated integrals. The reader who can evaluate simple integrals can learn quickly from the examples how to deal with the iterated integrals used in the theory of expectation and conditional expectation. Appendix B provides a convenient compendium of mathematical facts used frequently in this work.

- Front Matter
- 1: Probability Systems
- 2: Minterm Analysis
- 3: Conditional Probability
- 4: Independence of Events
- 5: Conditional Independence
- 6: Random Variables and Probabilities
- 7: Distribution and Density Functions
- 8: Random Vectors and Joint Distributions
- 9: Independent Classes of Random Variables
- 10: Functions of Random Variables
- 11: Mathematical Expectation
- 12: Variance, Covariance, and Linear Regression
- 13: Transform Methods
- 14: Conditional Expectation, Regression
- 15: Random Selection
- 16: Conditional Independence, Given a Random Vector
- 17: Appendices
- Back Matter