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51. Lecture 16. B) Example: Coin Tossing‏‎ (3 revisions)
52. Lecture 9. B) Evaluating Estimators‏‎ (3 revisions)
53. Lecture 7. A) Random Sample‏‎ (3 revisions)
54. Full Lecture 15‏‎ (3 revisions)
55. Lecture 17. A) Ordinary Least Squares‏‎ (3 revisions)
56. Lecture 16. C) A More General Example‏‎ (3 revisions)
57. Full Lecture 4‏‎ (3 revisions)
58. Lecture 16. D) Conjugate Priors‏‎ (4 revisions)
59. Lecture 6. F) Covariance and Correlation‏‎ (4 revisions)
60. Lecture 9. F) Factorization Theorem‏‎ (4 revisions)
61. Lecture 7. C) Order Statistics‏‎ (4 revisions)
62. Lecture 7. B) Statistics‏‎ (4 revisions)
63. Lecture 11. G) Setting the Critical Value‏‎ (4 revisions)
64. Lecture 13. G) Interval Estimation/Confidence Intervals‏‎ (4 revisions)
65. Lecture 13. F) Some Notes‏‎ (4 revisions)
66. Lecture 8. C) Maximum Likelihood‏‎ (4 revisions)
67. Lecture 14. E) Central Limit Theorem‏‎ (4 revisions)
68. Lecture 5. C) Multiple Random Variables‏‎ (4 revisions)
69. Lecture 18. C) Gauss-Markov Theorem‏‎ (4 revisions)
70. Lecture 17. B) Normal Linear Model‏‎ (4 revisions)
71. Lecture 6. D) Law of Iterated Expectations‏‎ (4 revisions)
72. Lecture 12. H) Equivalence Between LRT and Wald Tests‏‎ (4 revisions)
73. Lecture 11. B) Testing Procedure‏‎ (4 revisions)
74. Lecture 3. A) Expected Value‏‎ (4 revisions)
75. Lecture 11. E) Power Function‏‎ (4 revisions)
76. Lecture 3. B) Moments‏‎ (4 revisions)
77. Lecture 16. E) Normal Distribution‏‎ (4 revisions)
78. Lecture 15. A) Asymptotic Properties of ML Estimators‏‎ (4 revisions)
79. Lecture 12. D) Wald Test‏‎ (5 revisions)
80. Lecture 4. E) Uniform‏‎ (5 revisions)
81. Lecture 11. C) Variation on a Theme‏‎ (5 revisions)
82. Lecture 12. C) Lagrange Multiplier Test‏‎ (5 revisions)
83. Lecture 12. G) Equivalence Between LRT and LM Tests‏‎ (5 revisions)
84. Lecture 6. C) Conditional Moments‏‎ (5 revisions)
85. Lecture 11. F) Example 1‏‎ (5 revisions)
86. Lecture 14. A) Convergence‏‎ (5 revisions)
87. Lecture 15. C) Example: Hypothesis Test‏‎ (6 revisions)
88. Lecture 6. A) Multiple Random Variables (cont.)‏‎ (6 revisions)
89. Lecture 17. C) Asymptotic Properties of OLS‏‎ (6 revisions)
90. Lecture 13. B) Example: Normal‏‎ (6 revisions)
91. Lecture 2. B) Leibniz Rule II‏‎ (6 revisions)
92. Lecture 10. A) Finding UMVU Estimators‏‎ (6 revisions)
93. Lecture 12. E) Example: LRT‏‎ (6 revisions)
94. Lecture 15. E) Multiple Parameters‏‎ (6 revisions)
95. Lecture 13. E) p-value‏‎ (6 revisions)
96. Lecture 11. D) Testing Errors‏‎ (6 revisions)
97. Lecture 4. C) Binomial‏‎ (6 revisions)
98. Lecture 12. J) Neyman-Pearson Lemma‏‎ (6 revisions)
99. Lecture 1. D) Probability Space‏‎ (6 revisions)
100. Lecture 3. C) Moment Generating Function‏‎ (7 revisions)

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