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  1. (hist) ‎Lecture 14. C) Convergence in Distribution ‎[2,267 bytes]
  2. (hist) ‎Lecture 14. B) Law of Large Numbers ‎[2,275 bytes]
  3. (hist) ‎Lecture 11. A) Hypothesis Testing ‎[2,286 bytes]
  4. (hist) ‎Lecture 5. C) Multiple Random Variables ‎[2,356 bytes]
  5. (hist) ‎Lecture 10. A) Finding UMVU Estimators ‎[2,358 bytes]
  6. (hist) ‎Lecture 12. H) Equivalence Between LRT and Wald Tests ‎[2,369 bytes]
  7. (hist) ‎Lecture 6. G) Some Inequalities ‎[2,423 bytes]
  8. (hist) ‎Lecture 1. A) Sample Space ‎[2,436 bytes]
  9. (hist) ‎Lecture 4. D) Poisson ‎[2,462 bytes]
  10. (hist) ‎Lecture 12. J) Neyman-Pearson Lemma ‎[2,466 bytes]
  11. (hist) ‎Lecture 16. E) Normal Distribution ‎[2,467 bytes]
  12. (hist) ‎Lecture 9. F) Factorization Theorem ‎[2,485 bytes]
  13. (hist) ‎Lecture 5. B) Chebychev's Inequality ‎[2,673 bytes]
  14. (hist) ‎Lecture 7. C) Order Statistics ‎[2,718 bytes]
  15. (hist) ‎Lecture 12. I) Optimal Tests ‎[2,721 bytes]
  16. (hist) ‎Lecture 18. A) Multicollinearity ‎[2,721 bytes]
  17. (hist) ‎Lecture 9. A) Point Estimation (cont.) ‎[2,909 bytes]
  18. (hist) ‎Lecture 17. D) Bootstrapping ‎[2,924 bytes]
  19. (hist) ‎Lecture 12. B) Likelihood-Ratio Test ‎[2,955 bytes]
  20. (hist) ‎Lecture 12. G) Equivalence Between LRT and LM Tests ‎[3,163 bytes]
  21. (hist) ‎Lecture 1. E) More on Probability Functions ‎[3,243 bytes]
  22. (hist) ‎Lecture 16. B) Example: Coin Tossing ‎[3,265 bytes]
  23. (hist) ‎Lecture 11. B) Testing Procedure ‎[3,327 bytes]
  24. (hist) ‎Lecture 17. A) Ordinary Least Squares ‎[3,399 bytes]
  25. (hist) ‎Lecture 16. C) A More General Example ‎[3,461 bytes]
  26. (hist) ‎Lecture 9. E) Rao-Blackwell ‎[3,498 bytes]
  27. (hist) ‎Lecture 4. F) Gamma ‎[3,758 bytes]
  28. (hist) ‎Lecture 15. C) Example: Hypothesis Test ‎[3,874 bytes]
  29. (hist) ‎Lecture 16. G) Multiple Observations ‎[3,936 bytes]
  30. (hist) ‎Lecture 1. B) Probability Function ‎[3,939 bytes]
  31. (hist) ‎Lecture 11. G) Setting the Critical Value ‎[3,944 bytes]
  32. (hist) ‎Lecture 4. H) Dirac delta function ‎[3,966 bytes]
  33. (hist) ‎Lecture 13. D) 2-sided Tests and Unbiased Tests ‎[4,048 bytes]
  34. (hist) ‎Lecture 11. C) Variation on a Theme ‎[4,064 bytes]
  35. (hist) ‎Lecture 14. E) Central Limit Theorem ‎[4,168 bytes]
  36. (hist) ‎Lecture 18. C) Gauss-Markov Theorem ‎[4,180 bytes]
  37. (hist) ‎Lecture 12. E) Example: LRT ‎[4,207 bytes]
  38. (hist) ‎Lecture 13. E) p-value ‎[4,224 bytes]
  39. (hist) ‎Lecture 11. D) Testing Errors ‎[4,309 bytes]
  40. (hist) ‎Lecture 10. C) Cramer-Rao Lower Bound ‎[4,328 bytes]
  41. (hist) ‎Lecture 11. F) Example 1 ‎[4,334 bytes]
  42. (hist) ‎Lecture 1. F) Random Variables ‎[4,452 bytes]
  43. (hist) ‎Lecture 2. C) Transformations of Random Variables ‎[4,455 bytes]
  44. (hist) ‎Lecture 1. C) Domain of Probability Function ‎[4,829 bytes]
  45. (hist) ‎Lecture 14. F) Delta Method ‎[4,835 bytes]
  46. (hist) ‎Lecture 7. B) Statistics ‎[4,898 bytes]
  47. (hist) ‎Lecture 13. G) Interval Estimation/Confidence Intervals ‎[5,071 bytes]
  48. (hist) ‎Lecture 9. D) Sufficient Statistics ‎[5,114 bytes]
  49. (hist) ‎Lecture 2. A) Random Variables (cont.) ‎[5,208 bytes]
  50. (hist) ‎Lecture 8. C) Maximum Likelihood ‎[5,244 bytes]

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