This course is a follow-on course to our Introductory Statistics course, including some topics that have been suggested by previous attendees. This course assumes basic knowledge of statistics and use of R, which would be obtained from our Introductory Statistics Course and Introduction to Solving Biological Problems with R run at the Genetics department (or equivalent). The course will cover linear regression, ANOVA and non-parametric ANOVA. It will be a mixture of lectures and hands-on time using RStudio to analyse data.
Course Materials
Cheatsheet of when to use each statistical test (pdf)
Manual (pdf) (R Script)
Lecture Slides ANOVA (pdf) Non-Parametic Methods (pdf) Linear Regression (pdf)
Online Quiz
R Practical
Course Data (.zip)
Topics
Select an appropriate test for analysing data
Analyse data using linear regression
Check the assumptions of linear regression are met by the data
Check the fit of the linear regression model to your data
Know when linear regression is not appropriate and have an idea of which alternative method might be appropriate
Analyse data using ANOVA
Know how to check that the ANOVA assumptions are met by the data
Know when to use which non-parametric version of ANOVA
Analyse data using non-parametric ANOVA
Know when you need to seek help with analysis as the data structure is too complex for the methods taught