| Date | Chapter | Description |
|
| Jan 19 | 1.9 | Introduction, mgfs, and review |
| Jan 21 | 1.9, 2.5, 3.1 | More mgfs |
|
| Jan 24 | 3.4 | Normal random variables: sums and CLT |
| Jan 26 | 3.3 | The Gamma distribution and friends |
| Jan 28 | 3.3, 3.6 | The Chi squared and Student t-distributions |
|
| Jan 31 | 3.6, 4.1 | Moments of t-distributions, sample distributions |
| Feb 2 | 3.6 | t-distributions from samples and the t-test |
| Feb 4 | 3.6 | F-distributions, homework solutions |
|
| Feb 7 | 3.4.1, 3.7, 4.1 | Mixture distributions, Statistics |
| Feb 9 | 4.1, 5.1 | Unbiased estimator examples |
| Feb 11 | 5.1 | Confidence intervals |
|
| Feb 14 | 5.1, 5.2 | More confidence intervals, order statistics |
| Feb 16 | 5.2 | Order statistic pdfs and joint pdfs |
| Feb 18 | 5.2 | Order statistics as estimators |
|
| Feb 21 | 5.7 | Chi-squared statistics |
| Feb 23 | 5.7 | Chi-squared statistics -- GOF |
| | Exam 1 due |
| Feb 25 | 5.7 | Chi-squared statistics -- independence |
|
| Feb 28 | 6.1 | Maximum likelihood -- Bernoulli example |
| Mar 2 | 6.1 | Maximum likelihood -- asymptotic maximality of theta_real |
| Mar 4 | 6.1 | Mle examples |
|
| Mar 7 | 6.1 | Mles are preserved under 1-1 transformations |
| Mar 9 | 6.1 | Statement of convergence of mles -> theta_real |
| Mar 11 | 6.1 | Proof of convergence of mles -> theta_real |
|
| Mar 14 | | Spring Break! (no class) |
| Mar 16 | | Spring Break! (no class) |
| Mar 18 | | Spring Break! (no class) |
|
| Mar 21 | 6.2 | Overview of 6.2 ideas |
| Mar 23 | 6.2 | Score functions and Fisher information |
| Mar 25 | 6.2 | Fisher information example, statement of Rao-Cramer |
|
| Mar 28 | 6.2 | Proof of Rao-Cramer, Bernoulli examples |
| Mar 30 | 6.2 | CLT for mles, proof (Andy Womack) |
| Apr 1 | 6.2 | CLT for mles and KL divergence (Andy Womack) |
|
| Apr 4 | 6.2 | what (R5) means, and how to check it |
| Apr 6 | 6.2 | the big ideas in the CLT for mles proof |
| | Exam 2 due |
| Apr 8 | 6.2 | Asymptotic efficiency, ARE |
|
| Apr 11 | 6.2 | ARE examples: Laplace and normal |
| Apr 13 | 6.2 | hw solutions |
| Apr 15 | 6.2 | Differentiating under the integral sign (Kabe Moen) |
|
| Apr 18 | 6.3 | Wald tests, likelihood ratio test |
| Apr 20 | 6.3 | Likelihood ratio statistic, asymptotic distribution |
| Apr 22 | 6.3 | Scores test, asymptotic equivalency of likelihood tests |
|
| Apr 25 | 6.4 | 2-parameter mles for normal random variables |
| Apr 27 | 6.4 | 2-parameter Fisher information for normals, CLT for medians |
| Apr 29 | - | CLT for medians |
|
| May 9 | Final exam (6:00 pm - 8:00 pm, January 110) |