Introduction to probability 2nd_edition-textbook+solution
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. Discrete Random Variables

• 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
  

3. General Random Variables
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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
  

5. Limit Theorems
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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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