| 2026-01-12 |
1 |
(Section 2.4) What is probability? |
| 2026-01-14 |
2 |
(Sections 2.7, 2.11, 4.2) Independent events, conditional probabilites, random variables |
| 2026-01-16 |
3 |
(Section 4.2, 5.4) Random variables, expected value, joint distributions, independence |
| 2026-01-21 |
4 |
Independence of random variables |
| 2026-01-23 |
5 |
Weak law of large numbers, identical distribution, populations |
| 2026-01-26 |
6 |
(Sections 2.12, 6.1, 7.1) What is a statistic? What is a random sample? |
| 2026-01-28 |
7 |
(Section 7.1) Basic examples of statistics and estimators |
| 2026-01-30 |
8 |
(Section 7.2) The Gaussian distribution |
| 2026-02-02 |
9 |
(Section 7.2) Chi-squared distribution, t-distribution |
| 2026-02-04 |
10 |
(Section 7.2) t-distribution |
| 2026-02-06 |
11 |
(Sections 7.3, 7.4) The Central Limit Theorem, point estimation |
| 2026-02-11 |
12 |
(Sections 8.2, 8.3, 8.4) Mean square error, standard error |
| 2026-02-13 |
13 |
??? |
| 2026-02-18 |
|
In-class Midterm 1 |
| 2026-02-20 |
|
R coding worksheet |
| 2026-02-23 |
14 |
(Sections 8.5, 8.6) Confidence intervals, large-sample confidence intervals |
| 2026-02-25 |
15 |
(Sections 8.6, 8.7) Large-sample confidence intervals, sample complexity |
| 2026-02-27 |
16 |
(Section 9.3) Small-sample confidence intervals, consistency |
| 2026-03-02 |
17 |
(Section 9.2) Relative efficiency |
| 2026-03-04 |
18 |
(Section 9.4) Sufficiency, factorization criterion |
| 2026-03-06 |
19 |
(Section 9.4) Applications of the factorization criterion |
| 2026-03-09 |
20 |
(Section 9.5) The Rao-Blackwell theorem, MVUE |
| 2026-03-11 |
21 |
(Section 9.7) Maximum likelihood estimation |
| 2026-03-23 |
22 |
(Section 10.2) Hypothesis testing, decision errors |
| 2026-03-25 |
23 |
(Section 10.3) Large sample hypothesis tests |
| 2026-03-27 |
24 |
(Section 14.2-14.4) Chi-squared hypothesis tests |
| 2026-03-30 |
|
hypothesis-testing-worksheet (tex-file) |
| 2026-04-01 |
|
In-class Midterm 2 |
| 2026-04-06 |
25 |
(Section 10.10) Power function, simple/composite hypotheses, Neyman-Pearson Lemma |
| 2026-04-08 |
26 |
A geometric perspective on statistical models |
| 2026-04-13 |
27 |
The likelihood ratio test |
| 2026-04-15 |
28 |
Linear regression |
| 2026-04-17 |
29 |
General linear model, normal equations, least squares regression |
| 2026-04-20 |
30 |
General linear model recap |
| 2026-04-22 |
31 |
Examples of finding least squares estimates, overfitting |
| 2026-04-24 |
32 |
Properties of least squares estimators, evaluating inferences made with linear regression |
| 2026-04-27 |
33 |
Distribution of test statistic for LSE, equivalence of MLE and LSE, introduction to logistic regression |
| 2026-04-29 |
34 |
Logistic regression |
| 2026-05-01 |
35 |
Logistic regression with multiple covariates, intro to method of moments |
| 2026-05-03 |
36 |
Method of moments |
| 2026-05-06 |
37 |
Consistency of the method of moments |