The aim of this course is to provide an understanding of the statistical principles underlying experimentation. A proper set-up of an experiment is of utmost importance to be able to draw statistically sound conclusions.
The role of sample size, randomization and the reduction of unwanted noise factors will be highlighted. The way errors propagate will be discussed. The difference between experimental unit and measurement units and consequences for statistical analysis will be discussed.
Examples of basic designs (CRD, RCBD, BIBD), but also more advanced designs will be discussed. Lectures will be interchanged with computer practicals, using R. The final half day will be devoted to discussion of the own experimental designs of the participants.
Former occurrences of this course
26-28 Jan 2022 | 16-18 Dec 2020 | 21-23 May 2019 | 19-21 Dec 2018 | 23-25 May 2018 | 20-22 Dec 2017 | 19-23 May 2017 | 19-21 Dec 2016