by Dimitri P. Bertsekas and John N. Tsitsiklis
MIT 2008
Good quality, believe me!!!
What's more, the textbook.pdf has title labels as follows. (…………………… because of word limit of this forum )
1. Sample Space and Probability
- 1.1. Sets
- 1.2. Probabilistic Models
- 1.3. Conditional Probability
- 1.4. Total Probability Theorem and Bayes' Rule
- 1.5. Independence
- 1.6. Counting
- 1.7. Summary and Discussion
- Problems
- 2.1. Basic Concepts
- 2.2. Probability Mass Functions
- 2.3. Functions of Random Variables
- 2.4. Expectation, Mean, and Variance
- 2.5. Joint PMFs of Multiple Random Variables
- 2.6. Conditioning
- 2.7. Independence
- 2.8. Summary and Discussion
- Problems
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4. Further Topics on Random Variables
- 4.1. Derived Distributions
- 4.2. Covariance and Correlation
- 4.3. Conditional Expectation and Variance Revisited
- 4.4. Transforms
- 4.5. Sum of a Random Number of Independent Random Variables
- 4.6. Summary and Discussion
- Problems
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6. The Bernoulli and Poisson Processes
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7. Markov Chains
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8. Bayesian Statistical Inference
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9. Classical Statistical Inference
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- Introduction to probability 2nd_edition-solution.pdf
- Introduction to probability 2nd_edition.pdf