Introduction to statistical modelling in R

This is a one day intensive course on modelling in R. The course will be a mixture of lectures and computer practicals.

Prior knowledge: it will be assumed that participants are familiar with R. For example, inputting data, basic visualisation and data frames. Attending the introduction to R will be sufficient. This course is suitable to a wide range of applicants e.g., biologists, statisticians, engineers, students.

Course outline:

  • Basic hypothesis testing: examples include one-sample t-test, one-sample Wilcoxon signed-rank test, independent two-sample t-test, Mann-Whitney test, two-sample t-test for paired samples, Wilcoxon signed-rank test.
  • ANOVA tables: 1-way and 2-way tables.
  • Simple and multiple linear regression: including model diagnostics.
  • Clustering: hierarchical clustering, kmeans.
  • Principal components analysis

Course Structure

This course is structured as follows:
  • 8:30 -- 9:00: Registration and coffee
  • 9:00 -- 10:15: Lecture
  • 10:15 -- 10:45: Lecture
  • 10:45 -- 12:15: Practical 1
  • 12:15 -- 1:15: Lunch (not provided)
  • 1:15 -- 2:40: Lecture
  • 2:40 -- 3:00: Coffee
  • 3:00 -- 4:45: Practical 2

These times are intended to give a flavour of how the course is run and so are subject to change.

Comments from previous courses

  • The balance between lectures and practicals was good.
  • Great help during the practicals.
  • High quality lecture materials.


Dr Colin Gillespie, Statistics Lecturer in the School of Mathematics & statistics.