ANOVA with R
The aim of this short course is to explain why we have to analyse variances if we want to compare group means using ANOVA techniques. This lecture may be included in the Linear regression with R course. Please note that we cannot go into the specific data analysis problems of your particular project.
Instructor: András Aszódi.
Topics
- Comparing the means of several samples by analyzing variances: the intuition behind ANOVA.
- One-way ANOVA techniques: prerequisites, omnibus F-test, post hoc tests.
- Combination of effects: two-way ANOVA.
Out of scope
This course will not teach you bioinformatics. In particular, no high-throughput sequencing data will be used because they are impractically large, and not everyone on campus is working with sequencing.
If you are interested in the statistical background of gene expression analysis with high-throughput sequencing, then please take our RNA-Seq data analysis course.
Prerequisites
Participants should have a good understanding of basic statistics. Our Statistics with R course helps you refresh your stats skills.
Basic familiarity with R is advantageous, in particular:
- Using the R Studio environment
- How to invoke R functions, pass optional/named parameters
- Some familiarity with simple plotting commands
If you have attended our R as a programming language training then you are well equipped to take this course, but this is not a strict pre-requisite.
Practical information
Number of participants: minimum 5, maximum 10.
Length: The course takes one half-day, from 09:30 to 13:00 with one break.