Introduction to Linear Modelling with R
Description
The course will cover ANOVA, linear regression and some extensions. It will be a mixture of lectures and hands-on time using RStudio to analyse data.
Aims: During this course you will learn about:
- ANOVA
- Simple and multiple regression
- Generalised Linear Models
- Introduction to more advanced topics, like non-linear models and time series.
Objectives: After this course you should be able to
- Realise the connection between t-tests, ANOVA and linear regression
- Fit a linear regression
- Check if the assumptions of linear regression are met by the data and what to do if they are not
- Know when linear regression is not appropriate and have an idea of which alternative method might be appropriate
- Know when you need to seek help with analysis as the data structure is too complex for the methods taught
Course Data
- Please Download this zip file to have all the datasets and R files used in this course
Feedback
- After the course, please fill in this feedback form. Thank you.
Other courses
- The CRUK-CI Bioinformatics Core facility run a catalogue of courses. Please visit for more details.
Materials
- Course Introduction
- Tutorial HTML
- Tutorial R markdown
- Cheat Sheet PDF
- ANOVA
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Simple Regression
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Multiple Regression
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Generalised Linear Models
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Time Series Models
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
Pre-requisites
This course assumes basic knowledge of statistics and use of R , which would be obtained from our Introductory Statistics Course and an “Introduction to R for Solving Biological Problems” run at the Genetics department (or equivalent).