This course teaches the basics of R, an open-source and free environment for statistical analyses. In this course we also teach the basics transparent and reproducible research. For this, we teach RMarkdown, a tool to make dynamic reports in R.
The course assumes no previous knowledge of R or other programming tools, as well as no knowledge of statistics. This interactive course alternates short lectures with practicals, giving plenty of opportunity to learn by practicing.
In this course an introduction to basic statistical methods useful for biomedical data analysis will be given. During the course we will alternate between lectures and practicals, allowing for plenty of interaction and illustration with examples of practical interest.
The course requires little prior statistics knowledge, but assumes participants are able to work with R, R packages and RMarkdown for the practicals. Participants with no or little experience in R are strongly advised to follow an introductory R course prior to following this course, such as the one we offer.
The course program includes: exploratory data analysis, basic statistical tests, methods for count data tables, linear and logistic regression, as well as basic methods for survival data analysis. For each method, power analysis and sample size determination will be handled.
Please contact us for more information.