Exploring ANOVAs in R

R is quickly gaining popularity as a programming language for statisticians, data scientists and researchers. It has an excellent ecosystem including the powerful RStudio and the Shiny web application framework.This half-day course covers one and two-way Analyses of Variance (ANOVA) and their non-parametric counterparts in R.

ANOVA (Analysis of Variance) is a statistical method used to determine whether there are significant differences between the means of three or more groups. It helps analyse the effect of independent variables on a dependent variable by comparing the variance within groups to the variance between groups. ANOVA tests assume normality, homogeneity of variances, and independence of observations, and can be used to explore relationships in datasets, such as how factors like study time or parental education affect student performance.

• Basic statistical theory behind ANOVAs
• How to check that the data meets the assumptions
• One-way ANOVA in R and post-hoc analysis
• Two-way ANOVA plus interaction effects and post-hoc analysis
• Non-parametric alternatives to one and two-way ANOVA

This course assumes an intermediate level of programming proficiency, plus familiarity with the syntax and functions of the dplyr and ggplot2 packages. Experience navigating the RStudio integrated development environment (IDE) is also required.

If you’re new to programming in R, we strongly recommend you register for the \Learn to Program: R\, \Data Manipulation and Visualisation in R\ workshops first.