Basic statistics in R, Leuven - online
General context
The theory and demos of the four training days will be broadcasted on youtube.
Exercises and questions will be discussed in four separate session on Discord
Please register if you want to be informed on dates for the exercise sessions, and repeats of the training.
This training gives an introduction to the use of the statistical software language R. R is a language for data analysis and graphics. This introduction to R is aimed at beginners. The training covers data handling, graphics, and basic statistical techniques.
R is for free and for more information you can visit the CRAN web site.
This training is an introduction to the use of R and RStudio and stops at very basic analyses (t-tests and non-parametric equivalents). A full overview of statistical analyses in R including regression, ANOVA will be given in the follow-up training Basic statistics in R, part II.
- Get an idea of what R and Rstudio is
- Use R to handle data: creating, reading, reformatting and writing data
- Use R to create graphics
- Use basic statistical techniques in R : normality tests, t-tests, wilcoxon tests, chi square tests, correlations, survival analysis...
- Write and use R scripts
This training is recommended for people with no experience in R who are planning to follow a training that requires some R background, like the mass spectrometry training, the single cell RNA-Seq and the bulk RNA-Seq training....
The training is intended for people who have no experience with R. However, understanding of basic statistical concepts is required, such as data types, normal distribution, descriptive statistics, tests for comparing groups... If you don't have sufficient statistical background you are strongly encouraged to attend the Basic statistics theory training.
Trainers
Janick Mathys
Program
Introduction
Working with R and RStudio
Data structures
Operations on variables
Reading data from files
Descriptive statistics
Data reformatting
Graphics
Graphics
Basic statistical tests
Survival analysis
Correlation
Writing your own function