MATH3823 Generalized Linear Models

Author

Robert G Aykroyd

Published

May 6, 2024

Weekly schedule

Items will be added here week-by-week and so keep checking when you need up-to-date information on what you should be doing.

Week 11 (6 - 10 May)

Revision and examination preparation. Please do not forget that the examination this year is closed-book and all questions and you will be expected to attempt all questions.

Week 10 (29 April - 3 May)
  • Before next Lecture: Prepare for Exercises.
  • Lecture on Tuesday: Selected Exercises from Chapter 6.
  • Lecture on Thursday: Selected Exercises from Chapter 5.
Week 9 (22 - 26 April)
  • Submit your Computer Practical report on-time!
  • Before next Lecture: Re-read Chapter 6: Log-linear Models.
  • Lecture on Tuesday: Start Chapter 7: Extensions to Loglinear models.
  • Lecture on Thursday: Complete Chapter 7: Extensions to Loglinear models.
  • Weekly feedback: Check any previous Exercises and solutions not completed.
Advanced notice

Please note that I will not be available after Friday 22 March until Monday 22 April.

Assessed Practical
  • Module Assessment: Set on 12 March with submission deadline 23 April (that is after the break). You will be expected to write a short report based on an RStudio practical.
  • Computer classes: Supervised session on 19/20 March – check your timetable.
  • Generative AI usage within this module: The assessments for this module fall in the red category for using Generative AI which means you must not use Generative AI tools. The purpose and format of the assessments makes it inappropriate or impractical for AI tools to be used.
Week 8 (18 - 22 March)
  • Before next Lecture: Re-read Chapters 4 and 5 ready for practical.
  • Lecture on Tuesday: Start Chapter 6: Loglinear Modelling with Sections 6.1-6.3.
  • Computer Practical on Tuesday: Work on Assessed Practical.
  • Computer Practical on Wednesday: Work on Assessed Practical.
  • Lecture on Thursday: Complete Chapter 6: Loglinear Modelling with Section 6.4-6.5.
  • Weekly feedback: Start Exercises for Chapter 6 and check answers with solutions.
Week 7 (11 - 15 March)
  • Before next Lecture: Re-read Chapter 5: Sections 5.1-5.3.
  • Lecture on Tuesday: Complete Chapter 5: by looking at Section 5.5 - Application to dose-response experiments.
  • Lecture on Thursday: Consider selected Exercises from previous Chapters and discuss Assessed Practical. If time start Chapter 6: Log-linear Modelling.
  • Weekly feedback: Complete Exercises for Chapter 5.
Week 6 (4 - 8 March)
  • Before next Lecture: Re-read Chapter 4: Sections 4.1-4.2.
  • Lecture on Tuesday: Complete Chapter 4 with
    Sections: 4.3 Model deviance, 4.4 Model Residuals & 4.5 Fitting GLMs in R
  • Lecture on Thursday: Start Chapter 5: Modelling Proportions with Sections 5.1 & 5.2.
  • Weekly feedback: Complete Chapter 4 Exercises.
Week 5 (26 February - 1 March)
  • Before next Lecture: Re-read all of Chapter 3.
  • Computer Practical: Either on Tuesday or Wednesday, attend supervised computer class – see your timetable. For information see Week 5 Computer Practical folder on Minerva.
  • Lecture on Tuesday: Start Chapter 4 by covering Section 4.1: The identically distributed case.
  • Lecture on Thursday: Continue Chapter 4 with Section 4.2: The general case.
  • Weekly feedback: Check your answers on Chapter 3 Exercises with online solutions. Start Chapter 4 Exercises.
Week 4 (19 - 23 February)
  • Before next Lecture: Be confident with all material up to, and including, Section 3.2: The GLM structure.
  • Lecture on Tuesday: We will cover Section 3.3: The random part of a GLM, Section 3.4: Moments of exponential-family distributions and, if time permits, Sections 3.5: The systematic part of the model.
  • Lecture on Thursday: Complete Chapter 3 by covering Section 3.6: The link function. Then, we will consider selected Exercises from Section 3.7.
  • Weekly feedback: Complete Exercises in Chapter 3.
Week 3 (12 - 16 February)
  • Before next Lecture: Please re-read Section 2.5: Model shorthand notation and Section 2.6 Fitting linear models in R, and read Section 2.7: Ethics in statistics and data science.
  • Lecture on Tuesday: We will start Chapter 3 with Section 3.1: Motivating examples and Section 3.2: The GLM structure
  • Before next Lecture: Please re-read Sections 3.1 and 3.2 carefully.
  • Lecture on Thursday: CANCELLED due to illness.
  • Weekly feedback: Complete the first two Chapter 3 Quizzes and start the Exercises in Section 3.7.
Week 2 (5 - 9 February)
  • Before next Lecture: Please re-read Section 2.1: Overview and Section 2.2: Linear models, and read Section 2.3: Types of normal linear model.
  • Lecture on Tuesday: We will cover Section 2.4: Matrix representation of linear models and briefly Section 2.5: Model shorthand notation.
  • Before next Lecture: Please re-read Sections 2.4 and 2.5 carefully.
  • Lecture on Thursday: We will cover Section 2.6: Fitting linear models in R then discuss selected Exercises from Chapters 1 and 2.
  • Weekly feedback: Complete the Chapter 2 Quizzes and complete the Exercises in Section 2.8.
Week 1 (29 January - 2 February)
  • Before first Lecture: Please read the Overview.
  • Lecture on Tuesday: We will briefly cover all material in Chapter: Introduction.
  • Before next Lecture: Please re-read Chapter 1 carefully, especially any sections not covered in Lectures.
  • Lecture on Thursday: Start Chapter 2: Essentials of Normal Linear Models with Section 2.1: Overview & Section 2.2: Linear models.
  • Weekly feedback: Complete the Chapter 1 Quizzes and self-study the Exercises in Section 1.5. If you have time, start Exercises in Section 2.8.
Provisional Weekly Lecture Schedule1
Week 1 Chapter 1 All
Chapter 2 Sections 2.1-2.2
Week 2 Sections 2.3-2.7
Exercises Chapter 1 & 2
Week 3 Chapter 3 Sections 3.1-3.4
Week 4 Sections 3.5-3.6
Exercises Chapter 3
Week 5 Chapter 4 Sections 4.1-4.2
Week 6 Sections 4.3-4.5
Chapter 5 Sections 5.1-5.3
Week 7 Sections 5.4-5.5
Exercises Chapters 3 & 4
Week 8 Chapter 6 All
Easter
Week 9 Chapter 7 Sections 7.1-7.2
Week 10 Sections 7.3-7.4
Exercises Chapter 6 & 7
Week 11 Revision

  1. Some sections will be left as directed reading, but please note that material in all sections is examinable.↩︎