Statistical Modelling (Part II, Michaelmas 2021)

General information

  • This course consists of 16 lectures and 8 practical sessions. It complements the Part II Principles of Statistics, but takes a more applied perspective.

  • Prerequisites: Part IB Statistics.

  • Location: MR5.

  • Please email me or leave a comment below if you find any mistakes or have any questions.

  • Lectures will be recorded and the recordings can be found on Moodle.


By Chapter


Lecture Notes on Statistical Modelling.


Number Date Topic Optional Reading
P1 <2021-10-9 Sat> Basic R; Solution CRAN Intro to R 1,2,5,8
P2 <2021-10-16 Sat> Writing functions, linear models; Code; Solution CRAN Intro to R 6, 10
P3 <2021-10-23 Sat> Linear models; Code CRAN Intro to R 11.1–3
P4 <2021-10-30 Sat> Model selection; Code; Solution
P5 <2021-11-06 Sat> ANOVA and ANCOVA; Code; Solution 2019 notes 1.2.5
P6 <2021-11-13 Sat> Binomial GLMs; Code; Solution
P7 <2021-11-20 Sat> Binomial and Poisson GLMs; Code; Solution
P8 <2021-11-27 Sat> Contigency tables and Gamma GLMs; Code; Solution Agresti 4.7

Example sheets


Theory for LM and GLM

R and statistical computing

  • W. N. Venables, D. M. Smith and the R Core Team. An Introduction to R.

  • H. Wickham. Advanced R (for anyone who wants to really understand R as a programming language).

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