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

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).

• Introduction to Solving Biological Problems with R
• Introduction to Statistical Analysis