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Lecture 1: Probability and Counting | Statistics 110
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Statistics 110 - Probability
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- 1 Lecture 1: Probability and Counting | Statistics 110
- 2 Lecture 2: Story Proofs, Axioms of Probability | Statistics 110
- 3 Lecture 3: Birthday Problem, Properties of Probability | Statistics 110
- 4 Lecture 4: Conditional Probability | Statistics 110
- 5 Lecture 5: Conditioning Continued, Law of Total Probability | Statistics 110
- 6 Lecture 6: Monty Hall, Simpson's Paradox | Statistics 110
- 7 Lecture 7: Gambler's Ruin and Random Variables | Statistics 110
- 8 Lecture 8: Random Variables and Their Distributions | Statistics 110
- 9 Lecture 9: Expectation, Indicator Random Variables, Linearity | Statistics 110
- 10 Lecture 10: Expectation Continued | Statistics 110
- 11 Lecture 11: The Poisson distribution | Statistics 110
- 12 Lecture 12: Discrete vs. Continuous, the Uniform | Statistics 110
- 13 Lecture 13: Normal distribution | Statistics 110
- 14 Lecture 14: Location, Scale, and LOTUS | Statistics 110
- 15 Lecture 15: Midterm Review | Statistics 110
- 16 Lecture 16: Exponential Distribution | Statistics 110
- 17 Lecture 17: Moment Generating Functions | Statistics 110
- 18 Lecture 18: MGFs Continued | Statistics 110
- 19 Lecture 19: Joint, Conditional, and Marginal Distributions | Statistics 110
- 20 Lecture 20: Multinomial and Cauchy | Statistics 110
- 21 Lecture 21: Covariance and Correlation | Statistics 110
- 22 Lecture 22: Transformations and Convolutions | Statistics 110
- 23 Lecture 23: Beta distribution | Statistics 110
- 24 Lecture 24: Gamma distribution and Poisson process | Statistics 110
- 25 Lecture 25: Order Statistics and Conditional Expectation | Statistics 110
- 26 Lecture 26: Conditional Expectation Continued | Statistics 110
- 27 Lecture 27: Conditional Expectation given an R.V. | Statistics 110
- 28 Lecture 28: Inequalities | Statistics 110
- 29 Lecture 29: Law of Large Numbers and Central Limit Theorem | Statistics 110
- 30 Lecture 30: Chi-Square, Student-t, Multivariate Normal | Statistics 110
- 31 Lecture 31: Markov Chains | Statistics 110
- 32 Lecture 32: Markov Chains Continued | Statistics 110
- 33 Lecture 33: Markov Chains Continued Further | Statistics 110
- 34 Lecture 34: A Look Ahead | Statistics 110
- 35 Joseph Blitzstein: "The Soul of Statistics" | Harvard Thinks Big 4
