WIAS/PE&RC Course Design of Experiments

Course description

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.

Learning goals

• Understanding the principles of experimental design: the role of sample size, randomization and reduction of noise factors in the efficient set-up of experiments
• Experimental units vs measurement units, and consequences for statistical analysis
• Examples of commonly used experimental designs, and some more advanced designs

General Information

Target Group	PhD candidates
Course level	In-depth, post graduate
Group size	A minimum of 15 and a maximum of 24 participants
Course duration	2.5 days and given twice per year
Prior knowledge	Basic knowledge about statistics: summary statistics,  parameter estimation, hypothesis testing, t-tests, simple regression, one-way ANOVA (will be refreshed)
Home work/ self- study	Preparing a short presentation of own experimental design (0.5 hour)
Language	English
Credit points	0.8 ECTS
Name lecturers	Gerrit Gort and Evert-Jan Bakker (both from Mathematical and Statistical Methods Group, WUR)
Teaching methods	Lectures, computer practicals, discussions
In-person	Wageningen University campus, Wageningen, the Netherlands. Note: Room and building will be communicated to registered and confirmed participants about one week before the start of the course.

 

Programme

Day 1:

09.00-10.45 Session 1: Refresher statistics: summary statistics, t-tests, regression and ANOVA; statistical software R; basic design: three R’s & terminology

11.00-12.30 Session 2: R1: Replication: power and sample size

12.30-13.30 Lunch

13.30-15.15 Session 3: Power and sample size (cont), principles of error propagation

15.30-17.00 Session 4: R2: Randomization

Day 2:

09.00-10.45 Session 5: R3: Reducing noise factors:  blocking and covariates; ANCOVA

11.45-12.30 Session 6: Special designs: CRD, RCBD, BIBD

12.30-13.30 Lunch

13.30-15.15 Session 7: Special designs: split-plot design; mixed models

15.30-17.00 Session 8: Special designs: Latin-squares, repeated measures situation, cross-over design; alpha design

Day 3:

9.00-10.45 Session 9: Apply to own case (groups of 4)

11.00-12.30 Session 10: Apply to and discuss own case (groups of 4); presentation 6x15 min

Fee (includes coffee/tea and lunches.)

Reduced fee: WUR PhD candidates with a TSP	€ 250
University fee: All other PhD candidates / post-docs and staff of Wageningen University	€ 500
External fee	€ 700

Cancellation condition

You may cancel free of charge up to 1 month before the start of the course. After this date you will be charged with the University fee. Unless: 

• You can find someone to replace you in the course and supply the course coordinator with the name and contact information of your replacement. In this case you will be charged a €50,- cancellation fee.
• PhDs of Wageningen University who have a valid reason to cancel (illness or death in the family 1st or 2nd degree). In this case you will be charged the reduced fee and your supervisor/PI must send a mail indication the reason for cancellation.

Information

For more information please contact:

paddy.haripersaud@wur.nl, tel: +31317486836 or wias@wur.nl