A student's guide to MATH5806 at UNSW: generalised linear models in R, the Dobson & Barnett textbook, assessment breakdown (quiz, R assignment, mid-session, final), plus free notes and fully worked GLM solutions.
R
2026-09-13
Lab 2
The Chapter 2 lab is a tour of the language itself – vectors, matrices, indexing, plotting, and loading a data set. What follows is that tour, split into the sections the book uses.
Basic Commands
Vectors are built with c() (concatenate), and both <- and = assign. Arithmetic is element-wise, so operands must share a length – reassigning x to length 3 lets it line up with y:
Chapter 1: Getting Started
mean(abs(rnorm(100))) # generate 100 N(0,1) variates, take abs, then mean
rnorm(10)
Chapter 2: Vectors
Chapter 3: Matrices and Arrays
Chapter 4: Lists
Chapter 5: Data Frames
Chapter 6: Factors and Tables
Chapter 7: R Programming Structures
Chapter 8: Doing Math and Simulations in R
Chapter 9: Object-Oriented Prgoramming
Chapter 10: Input/Output
Chapter 11: String Manipulation
Chapter 12: Graphics
Chapter 13: Debugging
Chapter 14: Performance Enhancement: Speed and Memory
Chapter 15: Interfacing R to Other Languages
Chapter 16: Parallel R
Worked solutions in R to all 78 exercises in the fourth edition of Dobson & Barnett's An Introduction to Generalized Linear Models — exponential family theory, estimation and inference, normal linear models, binomial and Poisson regression, contingency tables, survival analysis, clustered and longitudinal data, and Bayesian analysis with MCMC.