| Date | Class Topic | Reading (WMS) |
|---|---|---|
| 1/21 | Review of method of mgf for determining distributions | 7.1, 7.2 |
| 1/23 | Sampling distributions, chi-square, t-, F-distributions | 7.2 |
| 1/26 | Sampling distributions, cont. | 7.2 |
| 1/28 | Lab 1 | 7.3 |
| 1/30 | The Central Limit Theorem | 7.3 |
| 2/2 | Proof of CLT | 7.4 |
| 2/4 | An application -- normal approximation to binomial probabilities | 7.5 |
| 2/6 | Estimation basics | 8.1-8.4 |
| 2/9 | More on estimation basics | 8.1-8.4 |
| 2/11 | Confidence intervals | 8.5 |
| 2/13 | Additional examples | 8.5 |
| 2/16 | Large sample confidence intervals | 8.6 |
| 2/18 | Selecting sample size | 8.7 |
| 2/20 | Small sample confidence intervals for means | 8.8 |
| 2/23 | Lab 2 | 8.9 |
| 2/25 | Lab 2, continued | 8.9 |
| 2/27 | Midterm Exam 1 | Chapter 7, Chapter 8, sections 1 - 8 |
| 3/1 | Consistency of an estimator | 9.3 |
| 3/3 | Method of moments | 9.6 |
| 3/5 | Likelihood and sufficient statistics | 9.4 |
| 3/8,10,12 | No Class -- Spring Break | |
| 3/15 | Maximum likelihood estimation | 9.7 |
| 3/17 | More on maximum likelihood estimation | 9.7 |
| 3/19 | Statistical tests -- terminology and rationale | 10.1-2 |
| 3/22 | Large sample tests | 10.3 |
| 3/24 | Type II error probability and sample size | 10.4 |
| 3/26 | Relation to confidence intervals, Attained significance level | 10.5-6 |
| 3/29 | Small sample tests | 10.8 |
| 3/31 | Tests for variances | 10.9 |
| 4/2 | The Neyman-Pearson Lemma | 10.10 |
| 4/5 | Lab Project 3 | |
| 4/7 | Lab Project 3 | |
| 4/9,12 | No Class -- Easter Break | Chapter 11 |
| 4/14 | Linear models, regression | 11.1-11.2 |
| 4/16 | Midterm Exam 2 | Chapters 9, 10 |
| 4/19 | Least squares | 11.3 |
| 4/21 | Properties of least squares estimators | 11.4 |
| 4/23 | Inferences on parameters | 11.5 |
| 4/26 | Inferences on linear functions of parameters | 11.6 |
| 4/28 | Correlation | 11.8 |
| 4/30 | Lab Project 4 | |
| 5/3 | Lab Project 4, Course wrap-up |
Last modified: March 30, 2004