Course teacher: Roland Fuß
Timing and duration: October 2019 – may be repeated on demand
This course is conducted on six Fridays during the autumn semester. Course dates are 11.10., 25.10., 08.11., 22.11., 06.12., and 13.12, at 9:00-14:00 hrs (with lunch break).
To gain a course certificate, each participant is required to attend a minimum of four sessions.
Registrations: Course offer will be circulated by the institution mailing lists. Registration by email to Veronika Jorch (veronika.jorch@thuenende).
The registration is not open any more, the maximum number of participants has reached.
Target group: Mainly PhD students, but also other early-career researchers
Course description and learning aims:
The course is intended to prepare for typical statistical challenges encountered when analysing data from field and lab studies in agricultural and soil science. It will be focused on practical examples and be light on theory. The course will use R as a tool; rudimentary knowledge of R will be sufficient but it will be needed to follow the course when more advanced models are covered.
The course will start by revisiting undergrad-level statistics such as data exploration and descriptive statistics, distribution models, hypothesis tests, ANOVA. It will also cover some non-parametric statistics. The main focus will be on regression models: linear regression, robust regression, orthogonal regression, non-linear regression, non-gaussian error distributions (generalized linear models), modelling heterogeneity, dependency structures (mixed-effects models), generalized additive models.