Note that the list of topics is just a guideline, and that you are responsible for all material covered in lectures.
This list will be updated by the instructor by the end of the week in question (hopefully by Thursday). The homework questions will then be discussed in tutorial the following week -- they are not to be handed in, but doing them is essential for your understanding (which is what the tests will test). See also the textbook's selected answers file. For the computer exercises, see also the computing information.
| Week of | Topics (and corresponding textbook sections) | Homework questions |
| January 5 | Inference when probability distribution is known (5.2); or unknown (5.1, 5.5.3); Statistical models (5.3); Basic methods of estimation (5.5.1; omit Quantile Estimation). | 5.1.1, 5.1.5, 5.1.7, 5.2.4, 5.2.6, 5.2.10, 5.3.1, 5.3.2, 5.3.3, 5.3.5 (model only), 5.5.1 (omit (e)), 5.5.2 (omit (d)). |
| January 12 | Likelihood functions, MLE's, and the Score Equation (6.1, 6.2) | 6.1.2, 6.1.3, 6.1.4, 6.1.5, 6.1.20, 6.2.1, 6.2.2, 6.2.4, 6.2.6, 6.2.11, 6.2.15 |
| January 19 | Sufficient Statistics, Factorisation Theorem, Minimal Sufficient Statistics (6.1.1); Reparameterisation (6.2); Estimator Bias (6.3.1). | 6.1.6, 6.1.7, 6.1.13, 6.1.18, 6.2.3, 6.2.14, plus Extra Questions #1 and #2 (pdf) |
| January 26 | More re Bias (6.3.1). Mean Squared Error (6.3.1). Consistency. Intro to Confidence Intervals (6.3.2). | Extra Questions #3, #4, #5 (pdf); 6.3.1 and 6.3.3 (confidence intervals only) |
| February 2 | Confidence Intervals (6.3.2), Hypothesis Testing (6.3.3), Sample Size Calculations (6.3.4) | 6.3.1 and 6.3.3 (confidence intervals already done); 6.3.2, 6.3.4, 6.3.6, 6.3.8, 6.3.9, 6.3.10, 6.3.11, 6.3.12; plus optionally 6.3.15 and 6.3.16 (see computing information) |
| February 9 | More re Hypothesis Testing (6.3.3); Method of Moments (6.4.1; omit Delta Theorem); plus TEST #1 from 3-5 on Feb. 11 | Review previous week's questions re hypothesis testing; plus Extra Questions #6 and #7 (pdf); plus review Test #1 solutions (pdf) |
| February 16 | NONE: READING WEEK | NO CLASSES |
| February 23 | Introduction to Bayesian Inference (7.1) | 7.1.1, 7.1.2, 7.1.3, 7.1.4, 7.1.5, 7.1.6, 7.1.18, 7.2.1; plus Extra Question #8 (pdf); plus optionally 7.1.8 and 7.1.9 (see computing information) |
| March 1 | Model Checking and Ancilliary Statistics (9.1; omit Fisher's Exact Test and 9.1.1); Chi-Squared Goodness-of-Fit Test (9.1.2); Introduction to Catagorical Response Models (10.2.1) | 9.1.1, 9.1.5, 9.1.6; plus Extra Question #9 (pdf); plus 10.2.2; plus optionally 9.1.7 and 9.1.10 (see computing information) |
| March 8 | Catagorical Response Models (10.2.1), Least Squares Estimates (10.3.1), Introduction to Linear Regression (10.3.2) | 10.2.1, 10.2.3, 10.2.4, 10.2.5(a), 10.2.6(a), 10.2.10; 10.3.2, 10.3.4(b,i,j), 10.3.5(b), 10.3.6(b), 10.3.12 |
| March 15 | S^2 statistic, F statistic, ANOVA, RSS, ESS, R^2 statistic (10.3.2) | Remaining parts of 10.3.4, 10.3.5, and 10.3.6 [except may omit "residuals" parts, and may defer "confidence intervals" and "P-values" parts to following weeks]. |
| March 22 | Normal Linear Regression (10.3.2; omit "Analysis of Residuals"); plus TEST #2 from 3-5 on March 24 | "P-values" parts of 10.3.4, 10.3.5, and 10.3.6. Plus review the Test #2 solutions (pdf). |
| March 29 | Confidence intervals for Normal Linear Regression (10.3.2); One Categorical Predictor (10.4.1; omit the ANOVA decomposition and F statistic in this section). | "Confidence intervals" parts of 10.3.4, 10.3.5, and 10.3.6. Also 10.4.4(d), 10.4.5(d), and 10.4.6(d). |
| April 5 | No new topics. | Good luck and best wishes. |
The FINAL EXAM was three hours long, from 9:00 a.m. to 12:00 noon on Monday May 3, in University College, East Hall (surnames A-Li) and West Hall (surnames Ll-Z). See the Final Exam solutions (pdf).
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