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|An intuitive, algorithmic approach to probability and stochastic processes.|
Table of contents
1. The Language and Axioms of Probability.
3. Conditional Probability and Independence.
4. Discrete Random Variables.
5. Continuous Random Variables.
6. The Poisson Distribution and the Poisson Process.
7. Interlude: Modeling Randomness.
8. Joint Probability Distributions.
9. Variances, Covariances, Correlation Coefficients, and More on Expectations.
10. The Normal Distribution, Central Limit Theorem, and Law of Large Numbers.
11. Continuous-Time Birth and Death Processes.
12. Discrete-Time Markov Chains.
Appendix 1. Programming Terminology.
Appendix 2. Multiplying Square Matrices and a Vector Times a Matrix.
Appendix 3. Normal Distribution Table.
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Published by Pearson (March 31st 1987) - Copyright © 1987