Linear regression with R
The aim of this course is to teach you how to fit linear models to your data using R. We focus on linear regression and generalised linear models (GLMs) in order to improve your generic statistics knowledge. Please note that we cannot go into the specific data analysis problems of your particular project.
Instructor: András Aszódi.
- Fitting straight lines: single and multivariate linear regression, linearizing transformations.
- Fitting proportions and count data: generalized linear models.
- Comparing linear regressions: analysis of covariance (ANCOVA).
- Optionally this course may include the analysis of variance (ANOVA) lecture.
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.
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.
Number of participants: minimum 5, maximum 10.
Length: The course takes two half-days, from 09:00 to 13:00 with 2 breaks.