## 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
- Solution R markdown

- Simple Regression
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Solution R markdown

- Multiple Regression
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Solution R markdown

- Generalised Linear Models
- Slides PDF
- Tutorial HTML
- Tutorial R markdown
- Solution 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).