Probability Theory
Probability Theory Class Notes
Keywords: probability theory notes, Blitzstein and Hwang, sample spaces, counting, conditional probability, Bayes rule, random variables, expectation, variance, conditional expectation, central limit theorem.
As an instructor of introduction to probability theory, I prepared these PDFs as a review of the chapters in Introduction to Probability by Blitzstein and Hwang. They include example problems which have been worked out in some detail. I hope you find these useful.
| Class Notes |
In-Class Activities |
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| 1.1 thru 1.4 Sample Space, Naive Definition, Counting, Over Counting |
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| 1.5 1.6 Stories NonNaive |
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| 2.1 Think Conditionally |
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| 2.2 2.3 2.4 Conditional Probability, Bayes, LOTP |
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| 2.5 2.8 Independence, Coherency, Problem Solving, Pitfalls and Paradoxes |
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| 3.1 3.2 Random Variables, Distributions, Probability Mass Functions |
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| 3.3 3.5 Bernoulli, Binomial, Hypergeometric, Uniform |
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| 3.6 3.8 Cumulative Distribution Functions, Functions of RVs, Independence |
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| 4.1 4.3 Expectation, Linearity, Geometric, Negative Binomial |
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| 4.5 4.6 LOTUS, Variance |
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| 4.7 5.1 Poisson, Probability Density Functions |
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| 5.2 5.3 Uniform, Universality |
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| 5.4 5.5 Normal, Exponential |
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| 6.1 6.3 Distribution Summaries, Moments, Sample Moments |
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| 6.4 Moment Generating Functions |
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| 7.1 7.2 Joint Marginal, Conditional, 2D LOTUS |
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| 8.1 Change of Variables |
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| 9.1 9.2 Conditional Expectation |
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| 7.3 Covariance Correlation |
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| 10.1 10.2 Inequalities, Law of Large Numbers |
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| 10.3 Central Limit Theorem |
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