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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).

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Going beyond the t-test in R and introducing linear regression and ANOVA (http://tinyurl.com/linear-models-r)

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