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) [more]

Day 1: Indroduction Introduction o experimental design theory (difference between experiment and observation, confounding, importance of randomisation, types of experimental designs, implications for data analysis, power; practical: randomization with the software R, simple power calculations); Day 2: Applications - Each participant is asked to send a description of one planned experiment (or one running experiment if none is planned) to steffi.vonfelten@oikostat.ch until 30. September 2013 (e.g., drawing of the spatial layout and text description, what measurements are taken and when?). Course participants will present the design of their own experiments. Each experimental design will be discussed in class and will also receive some feedback by the course teacher. Prerequisite for participation: basic knowledge of statistics and the software package R would be an advantage but is not absolutely required. [more]