Intro to R and RStudio
Basic R syntax and data structure: access to elements (vectors, lists, dataframes)
Data handling and visualization
explore and manipulate data in R with “tidyverse”
use the R package “ggplot2” to visualize data an create plots
Hands-on: statistical tests with R on real data
IMPORTANT: Installation guide for R and RStudio
Introduction theory for point estimation, confidence interval, and hypothesis testing, Statistical significance, and p-value.
Tests on normal populations, the case of one sample, two independent samples, two paired samples, more than two samples, post-hoc tests.
Normality hypothesis testing, tests on non-normal populations, the case of two independent samples, two paired samples, more than two samples, post-hoc tests.
Nonparametric statistics
Adjusting for multiple testing
Basic theory on survival analysis.