Lecture 30: Chi-Square, Student-t, Multivariate Normal | Statistics 110

Lecture 31 of 36 in Probability (Harvard Stat 110) by stat110harvard. 47 min. Watch on YouTube

Course: Probability (Harvard Stat 110) (Mathematics). Covers: probability random variables bayes theorem distributions expectation variance conditional probability combinatorics.

All lectures in Probability (Harvard Stat 110)

  1. Joseph Blitzstein: "The Soul of Statistics" | Harvard Thinks Big 4 · 15 min
  2. Lecture 1: Probability and Counting | Statistics 110 · 46 min
  3. Lecture 2: Story Proofs, Axioms of Probability | Statistics 110 · 46 min
  4. Lecture 3: Birthday Problem, Properties of Probability | Statistics 110 · 49 min
  5. Lecture 4: Conditional Probability | Statistics 110 · 50 min
  6. Lecture 5: Conditioning Continued, Law of Total Probability | Statistics 110 · 50 min
  7. Lecture 6: Monty Hall, Simpson's Paradox | Statistics 110 · 49 min
  8. Lecture 7: Gambler's Ruin and Random Variables | Statistics 110 · 52 min
  9. Lecture 8: Random Variables and Their Distributions | Statistics 110 · 50 min
  10. Lecture 9: Expectation, Indicator Random Variables, Linearity | Statistics 110 · 50 min
  11. Lecture 10: Expectation Continued | Statistics 110 · 50 min
  12. Lecture 11: The Poisson distribution | Statistics 110 · 43 min
  13. Lecture 12: Discrete vs. Continuous, the Uniform | Statistics 110 · 50 min
  14. Lecture 13: Normal distribution | Statistics 110 · 51 min
  15. Lecture 14: Location, Scale, and LOTUS | Statistics 110 · 49 min
  16. Lecture 15: Midterm Review | Statistics 110 · 38 min
  17. Lecture 16: Exponential Distribution | Statistics 110 · 18 min
  18. Lecture 17: Moment Generating Functions | Statistics 110 · 51 min
  19. Lecture 18: MGFs Continued | Statistics 110 · 50 min
  20. Lecture 19: Joint, Conditional, and Marginal Distributions | Statistics 110 · 50 min
  21. Lecture 20: Multinomial and Cauchy | Statistics 110 · 49 min
  22. Lecture 21: Covariance and Correlation | Statistics 110 · 49 min
  23. Lecture 22: Transformations and Convolutions | Statistics 110 · 48 min
  24. Lecture 23: Beta distribution | Statistics 110 · 50 min
  25. Lecture 24: Gamma distribution and Poisson process | Statistics 110 · 49 min
  26. Lecture 25: Order Statistics and Conditional Expectation | Statistics 110 · 48 min
  27. Lecture 26: Conditional Expectation Continued | Statistics 110 · 50 min
  28. Lecture 27: Conditional Expectation given an R.V. | Statistics 110 · 51 min
  29. Lecture 28: Inequalities | Statistics 110 · 47 min
  30. Lecture 29: Law of Large Numbers and Central Limit Theorem | Statistics 110 · 50 min
  31. Lecture 30: Chi-Square, Student-t, Multivariate Normal | Statistics 110 · 47 min
  32. Lecture 31: Markov Chains | Statistics 110 · 47 min
  33. Lecture 32: Markov Chains Continued | Statistics 110 · 48 min
  34. Lecture 33: Markov Chains Continued Further | Statistics 110 · 47 min
  35. Lecture 34: A Look Ahead | Statistics 110 · 37 min
  36. Stat 110 Harvard - Let's Get Started (Statistics Song) · 3 min