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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