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.
- 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
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.