Introduction of basic statistics with R (Module 1)

day 1: introduction to R (work with console and editor, read in data, save data, basics in programming R, graphics, classical tests); day 2: basics in statistics (refreshing descriptive statistics (mean, sd, se, median, quartiles), introduction to different schools of statistics (frequentist, information theory, Bayes statistics), theory of statistical tests (example t-test and randomization test), classical tests (U-test, chi-test, binomial test, correlation, etc.); day 3: experimental design (basic theory in experimental design, presentation of an experimental design by each participant (own or prepared examples), discussion of experimental design, use R to plan experiments, power calculations)