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- 19:18, 4 December 2019 (diff | hist) (0) Lecture 18. C) Gauss-Markov Theorem (→Proof) (current)
- 15:12, 4 December 2019 (diff | hist) (-2) Lecture 18. C) Gauss-Markov Theorem (→Proof)
- 15:02, 4 December 2019 (diff | hist) (-15) Lecture 18. B) Partitioned Regression (→Partitioned Regression) (current)
- 14:57, 4 December 2019 (diff | hist) (-475) Lecture 18. A) Multicollinearity (→Multicollinearity) (current)
- 19:22, 3 December 2019 (diff | hist) (-51) Lecture 15. A) Asymptotic Properties of ML Estimators (→Asymptotic Properties of ML Estimators) (current)
- 19:20, 3 December 2019 (diff | hist) (-4) Lecture 17. C) Asymptotic Properties of OLS (→Implications of Strict Exogeneity) (current)
- 19:19, 3 December 2019 (diff | hist) (-5) Lecture 17. B) Normal Linear Model (→Log-likelihood of Y conditional on X) (current)
- 18:46, 2 December 2019 (diff | hist) (-28) Lecture 17. D) Bootstrapping (→Bootstrapping) (current)
- 18:42, 2 December 2019 (diff | hist) (+171) Lecture 17. C) Asymptotic Properties of OLS (→A note on the variance of \varepsilon_{i})
- 18:38, 2 December 2019 (diff | hist) (-6) Lecture 17. C) Asymptotic Properties of OLS (→Proof)
- 18:30, 2 December 2019 (diff | hist) (-80) Lecture 17. C) Asymptotic Properties of OLS (→Implications of Strict Exogeneity)
- 18:25, 2 December 2019 (diff | hist) (+5) Lecture 17. B) Normal Linear Model (→Normal Linear Model)
- 18:18, 2 December 2019 (diff | hist) (+61) Lecture 17. A) Ordinary Least Squares (→Ordinary Least Squares) (current)
- 15:04, 21 November 2019 (diff | hist) (+29) Lecture 15. C) Example: Hypothesis Test (→Tests) (current)
- 15:04, 21 November 2019 (diff | hist) (+1) Lecture 15. C) Example: Hypothesis Test (→Tests)
- 13:41, 20 November 2019 (diff | hist) (+1) Lecture 16. H) Theorem: Berstein von-Mises (→Theorem: Berstein von-Mises) (current)
- 13:36, 20 November 2019 (diff | hist) (+1) Lecture 16. F) "Counterexample" (current)
- 13:35, 20 November 2019 (diff | hist) (+42) Lecture 16. E) Normal Distribution (current)
- 13:35, 20 November 2019 (diff | hist) (+454) Lecture 16. E) Normal Distribution
- 13:31, 20 November 2019 (diff | hist) (+94) Lecture 16. D) Conjugate Priors (current)
- 13:26, 20 November 2019 (diff | hist) (+35) Lecture 16. B) Example: Coin Tossing (current)
- 12:47, 19 November 2019 (diff | hist) (-5) Lecture 15. E) Multiple Parameters (→Wald Test) (current)
- 12:45, 19 November 2019 (diff | hist) (-2) Lecture 15. E) Multiple Parameters (→Wald Test)
- 12:42, 19 November 2019 (diff | hist) (-12) Lecture 15. C) Example: Hypothesis Test (→Tests)
- 12:41, 19 November 2019 (diff | hist) (0) Lecture 15. C) Example: Hypothesis Test (→Information Matrix)
- 12:41, 19 November 2019 (diff | hist) (+4) Lecture 15. A) Asymptotic Properties of ML Estimators (→Asymptotic Properties of ML Estimators)
- 19:18, 18 November 2019 (diff | hist) (-8) Lecture 15. E) Multiple Parameters (→Example: Multiple Parameters)
- 14:19, 14 November 2019 (diff | hist) (-14) Lecture 14. E) Central Limit Theorem (→Proof) (current)
- 18:18, 13 November 2019 (diff | hist) (-21) Lecture 14. E) Central Limit Theorem (→Central Limit Theorem)
- 18:06, 13 November 2019 (diff | hist) (+57) Lecture 14. B) Law of Large Numbers (→Theorem: Law of Large Numbers) (current)
- 18:04, 13 November 2019 (diff | hist) (-157) Lecture 14. A) Convergence (→Convergence) (current)
- 17:42, 12 November 2019 (diff | hist) (-8) Lecture 13. E) p-value (current)
- 17:39, 12 November 2019 (diff | hist) (-11) Lecture 13. B) Example: Normal (→Example: Normal) (current)
- 06:02, 12 November 2019 (diff | hist) (+155) Lecture 9. D) Sufficient Statistics (→Remark: What does f\left(\left.X\right|\theta,T\right) mean?) (current)
- 15:03, 11 November 2019 (diff | hist) (+38) Lecture 13. G) Interval Estimation/Confidence Intervals (→Interval Estimation/Confidence Intervals) (current)
- 14:55, 11 November 2019 (diff | hist) (+73) Lecture 13. F) Some Notes (→The z-test: Using the Standardized Sample Mean as the Test (instead of the Sample Mean)) (current)
- 14:47, 11 November 2019 (diff | hist) (-48) Lecture 13. F) Some Notes (→z_{\alpha} Notation)
- 14:36, 11 November 2019 (diff | hist) (0) Lecture 13. E) p-value (→Definition)
- 14:36, 11 November 2019 (diff | hist) (-110) Lecture 13. E) p-value (→p-value)
- 14:23, 11 November 2019 (diff | hist) (+20) Lecture 13. D) 2-sided Tests and Unbiased Tests (→2-sided tests) (current)
- 14:18, 11 November 2019 (diff | hist) (+1) Lecture 13. B) Example: Normal (→Example: Normal)
- 14:18, 11 November 2019 (diff | hist) (+478) Lecture 13. B) Example: Normal (→Example: Normal)
- 17:57, 8 November 2019
(diff | hist)
**(-2,899)** Lecture 9. D) Sufficient Statistics - 17:56, 8 November 2019 (diff | hist) (+46) Lecture 9. D) Sufficient Statistics (→Remark: What does f\left(\left.X\right|\theta,T\right) mean?)
- 17:55, 8 November 2019
(diff | hist)
**(+2,513)** Lecture 9. D) Sufficient Statistics - 17:26, 8 November 2019 (diff | hist) (-377) Lecture 9. D) Sufficient Statistics (→Intuitive Example: Uniform)
- 16:25, 8 November 2019 (diff | hist) (0) Lecture 9. D) Sufficient Statistics (→Sufficient Statistics)
- 16:25, 8 November 2019 (diff | hist) (-4) Lecture 9. D) Sufficient Statistics (→Sufficient Statistics)
- 16:25, 8 November 2019 (diff | hist) (-216) Lecture 9. D) Sufficient Statistics (→Sufficient Statistics)
- 13:15, 4 November 2019 (diff | hist) (+21) Lecture 12. J) Neyman-Pearson Lemma (current)

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