Basic statistics in R
Basic statistics in R
11 August 2025 9h00-16h30
14 August 2025 9h00-12h30
25 August 2025 9h00-12h30
01 September 2025 9h00-16h30
General context
This course combines e-learning with online sessions
The course will consist of:
- a theoretical e-learning course to explain the statistics behind the analyses in R (not mandatory but recommended for those with some statistical knowledge)
- e-learning, where you will watch parts of the theory upfront
- demo and exercise sessions on YouTube, where your questions will be answered and where you can apply the theory to real-life example data
Since part of the course is done via e-learning, you have to consider that you will have to spend time on this course outside of class.
This introduction to the use of the free statistical software language R is aimed at beginners.
The training covers data handling, graphics, and basic statistical techniques (t-tests, one-way ANOVA, and non-parametric equivalents).
A complete overview of statistical analyses in R, including regression and two-way ANOVA, will be given in follow-up training.
By following this training, you will:
- Get an idea of what R and RStudio are
- Use R to handle data: creating, reading, reformatting, and writing data
- Use R to create graphics: bar charts, box, violin, scatter, PCA plots, heat maps, and various other plots
- Use basic statistical techniques in R: t-tests, Wilcoxon tests, one-way ANOVA, Kruskal-Wallis tests, chi-square tests, correlations, survival analysis...
- Write and use R scripts
- people with no prior experience in R planning to attend a training that requires some R background, such as genome engineering, single-cell RNASeq, linear mixed-model metagenomics, and bulk RNASeq.
None
- R
- RStudio
- various R packages
Trainers
Janick Mathys
Janick tries to help VIB scientists analyze their data by offering bioinformatics training and support. Next to organizing trainings, creating e-learning courses and teaching statistics, R, Python, Linux, HPC, bulk and single cell RNA-Seq analysis, she consults scientists and develops pipelines for omics analyses. Before joining VIB, she worked as a post-doc at KULeuven, doing research on transcriptomics and transcription regulation. She coordinated the Master of Bioinformatics program of KULeuven and taught the course on Biological Databases.