Statistics
Basic statistics theory
Trainer: Janick Mathys
Goal
After this basic statistics theory session, you should be able to:
- Understand basic statistical concepts and methods for statistical analysis of life sciences data
- Choose the correct statistical test for analyzing your data
- Interpret and critically assess the results of basic statistical analyses
Summary
This training gives an introduction to the use of statistics for basic analyses of life sciences data. This training is a prerequisite introduction to a series of hands-on trainings on the statistical analysis of life sciences data: 'Basic statistics in R' and 'Basic statistics in Graphpad Prism'. If you want to follow one of these trainings, you have to follow this introduction. It will give you all the theoretical background that you need.
Those that already have a strong statistical background may register directly for the 'Basic statistics in R, part II' training.
Prerequisites
None
Basic statistics in R
Trainer: Janick Mathys
Goal
- Get an idea of what R and R-Studio is, where to find more information, how to install and use it
- Use R to handle data: data types, reading data
- Use R to create graphics
- Use mathematical functions and basic statistical techniques in R
- Write and manage R scripts
Summary
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, mathematical functions and some statistical techniques. R is for free and for more information you can visit the site at 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
Prerequisites
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.
Linear and mixed effects models
Teacher: Joris De Wolf
Goals
in preparation, to be announced in March 2022
Required skills
If you have no experience with R you should follow our R introduction course.
Factorial design and analysis
Teacher: Joris De Wolf
Goals
After attending this course, you will be able to reason about your experiment and come up with a design and analysis that fits your situations best, rather than to settle for a suboptimal textbook solution.
Required skills
If you have no experience with R you should follow our R introduction course.
This course is a follow-up to the Experiment design course, so you should follow the Experiment design course first.