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1. Full Lecture 1
2. Full Lecture 10
3. Full Lecture 11
4. Full Lecture 12
5. Full Lecture 13
6. Full Lecture 14
7. Full Lecture 15
8. Full Lecture 16
9. Full Lecture 17
10. Full Lecture 18
11. Full Lecture 2
12. Full Lecture 3
13. Full Lecture 4
14. Full Lecture 5
15. Full Lecture 6
16. Full Lecture 7
17. Full Lecture 8
18. Full Lecture 9
19. Graduate Level: Intro to Probability and Statistics
20. Lecture 1. A) Sample Space
21. Lecture 1. B) Probability Function
22. Lecture 1. C) Domain of Probability Function
23. Lecture 1. D) Probability Space
24. Lecture 1. E) More on Probability Functions
25. Lecture 1. F) Random Variables
26. Lecture 10. A) Finding UMVU Estimators
27. Lecture 10. B) Complete Statistic
28. Lecture 10. C) Cramer-Rao Lower Bound
29. Lecture 11. A) Hypothesis Testing
30. Lecture 11. B) Testing Procedure
31. Lecture 11. C) Variation on a Theme
32. Lecture 11. D) Testing Errors
33. Lecture 11. E) Power Function
34. Lecture 11. F) Example 1
35. Lecture 11. G) Setting the Critical Value
36. Lecture 12. A) Statistical Tests
37. Lecture 12. B) Likelihood-Ratio Test
38. Lecture 12. C) Lagrange Multiplier Test
39. Lecture 12. D) Wald Test
40. Lecture 12. E) Example: LRT
41. Lecture 12. F) Test Equivalence
42. Lecture 12. G) Equivalence Between LRT and LM Tests
43. Lecture 12. H) Equivalence Between LRT and Wald Tests
44. Lecture 12. I) Optimal Tests
45. Lecture 12. J) Neyman-Pearson Lemma
46. Lecture 13. A) Test Optimality (cont.)
47. Lecture 13. B) Example: Normal
48. Lecture 13. C) Karlin-Rubin Theorem
49. Lecture 13. D) 2-sided Tests and Unbiased Tests
50. Lecture 13. E) p-value

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