Oldest pages

Jump to navigation Jump to search

Showing below up to 50 results in range #51 to #100.

View (previous 50 | next 50) (20 | 50 | 100 | 250 | 500)

  1. Lecture 1. A) Sample Space‏‎ (06:30, 24 September 2019)
  2. Lecture 2. A) Random Variables (cont.)‏‎ (20:55, 24 September 2019)
  3. Lecture 2. B) Leibniz Rule‏‎ (21:02, 24 September 2019)
  4. Lecture 2. C) Transformations of Random Variables‏‎ (21:08, 24 September 2019)
  5. Lecture 1. E) More on Probability Functions‏‎ (03:56, 26 September 2019)
  6. Lecture 1. F) Random Variables‏‎ (04:01, 26 September 2019)
  7. Lecture 3. A) Expected Value‏‎ (22:51, 30 September 2019)
  8. Lecture 3. C) Moment Generating Function‏‎ (23:15, 30 September 2019)
  9. Lecture 4. C) Binomial‏‎ (04:20, 2 October 2019)
  10. Lecture 4. D) Poisson‏‎ (04:22, 2 October 2019)
  11. Lecture 4. E) Uniform‏‎ (04:23, 2 October 2019)
  12. Lecture 4. H) Dirac delta function‏‎ (05:21, 2 October 2019)
  13. Lecture 4. B) Bernoulli‏‎ (22:12, 2 October 2019)
  14. Lecture 4. G) Normal‏‎ (22:20, 2 October 2019)
  15. Lecture 4. F) Gamma‏‎ (04:14, 3 October 2019)
  16. Lecture 5. A) Families of Distributions‏‎ (22:21, 7 October 2019)
  17. Lecture 5. C) Multiple Random Variables‏‎ (22:28, 7 October 2019)
  18. Lecture 6. B) Conditional PMF/PDF‏‎ (18:20, 9 October 2019)
  19. Lecture 6. C) Conditional Moments‏‎ (18:28, 9 October 2019)
  20. Lecture 6. D) Law of Iterated Expectations‏‎ (18:31, 9 October 2019)
  21. Lecture 6. E) Conditional Variance Identity‏‎ (18:32, 9 October 2019)
  22. Lecture 6. F) Covariance and Correlation‏‎ (18:34, 9 October 2019)
  23. Lecture 6. A) Multiple Random Variables (cont.)‏‎ (21:34, 10 October 2019)
  24. Lecture 6. G) Some Inequalities‏‎ (21:56, 10 October 2019)
  25. Lecture 7. A) Random Sample‏‎ (21:44, 14 October 2019)
  26. Lecture 7. B) Statistics‏‎ (21:51, 14 October 2019)
  27. Lecture 7. C) Order Statistics‏‎ (21:53, 14 October 2019)
  28. Lecture 8. A) Point Estimation‏‎ (17:20, 16 October 2019)
  29. Lecture 8. B) Method of Moments‏‎ (17:29, 16 October 2019)
  30. Lecture 8. C) Maximum Likelihood‏‎ (17:32, 16 October 2019)
  31. Lecture 9. B) Evaluating Estimators‏‎ (17:17, 21 October 2019)
  32. Lecture 9. C) Minimum Variance Estimators‏‎ (17:18, 21 October 2019)
  33. Lecture 9. F) Factorization Theorem‏‎ (17:48, 21 October 2019)
  34. Lecture 10. A) Finding UMVU Estimators‏‎ (17:33, 28 October 2019)
  35. Lecture 10. B) Complete Statistic‏‎ (20:11, 29 October 2019)
  36. Lecture 11. C) Variation on a Theme‏‎ (17:30, 30 October 2019)
  37. Lecture 11. D) Testing Errors‏‎ (17:35, 30 October 2019)
  38. Lecture 11. E) Power Function‏‎ (17:36, 30 October 2019)
  39. Lecture 11. F) Example 1‏‎ (17:41, 30 October 2019)
  40. Lecture 12. D) Wald Test‏‎ (17:46, 4 November 2019)
  41. Lecture 12. E) Example: LRT‏‎ (17:55, 4 November 2019)
  42. Lecture 12. G) Equivalence Between LRT and LM Tests‏‎ (17:59, 4 November 2019)
  43. Lecture 12. H) Equivalence Between LRT and Wald Tests‏‎ (18:02, 4 November 2019)
  44. Lecture 12. J) Neyman-Pearson Lemma‏‎ (18:15, 4 November 2019)
  45. Lecture 13. D) 2-sided Tests and Unbiased Tests‏‎ (19:23, 11 November 2019)
  46. Lecture 13. F) Some Notes‏‎ (19:55, 11 November 2019)
  47. Lecture 13. G) Interval Estimation/Confidence Intervals‏‎ (20:03, 11 November 2019)
  48. Lecture 9. D) Sufficient Statistics‏‎ (11:02, 12 November 2019)
  49. Lecture 13. B) Example: Normal‏‎ (22:39, 12 November 2019)
  50. Lecture 13. E) p-value‏‎ (22:42, 12 November 2019)

View (previous 50 | next 50) (20 | 50 | 100 | 250 | 500)

Retrieved from "https://significantstatistics.com/index.php/Special:AncientPages"