Factorial design and analysis

Factorial design and analysis


Park Inn, Leuven

Start date:

14 December 2020

14 December 2020
15 December 2020

General context


This is a face-to-face course


This training is organised in collaboration with the Helis Academy. More information see https://helisacademy.com/

Experimental research in life sciences can be complex. Understanding complicated biological processes, quantifying the influence of environmental parameters on the growth of an organism, getting to grips with simultaneous impacting factors and their interactions, optimizing research procedures or media recipes: all these require factorial experiments.

Factorial experiments can be very efficient, but the number of possible combinations quickly gets out of hand. Research facilities have limited capacity and have all sorts of constraints that do not fit the textbook solutions to factorial experiments.

In this course, realistic research cases form the starting point for which we will try to find practical solutions. We will tackle research questions by design tailor-made factorial experiments within the budget and lab constraints. Power analysis will be key to achieve this goal. Finally, we will analyse the expected output in a statistical sound manner, interpret the results and propose presentations.

Everything will be very practical and hands-on. Design and analysis happen in R. R code will be made available.

While discussing these practical cases, we will grab the opportunity to introduce the general principals of fractional factorial designs, optimal designs and their analysis and interpretation.

By this approach we hope to provide practical solutions while not too heavy dwelling on statistical theory.


After attending this course, you will be able to reason about you experiment and come up with a design and analysis that fits your situations best, rather than to settle for a suboptimal textbook solution.

Required skills

Basic principles of simple experimental design (replication, randomisation). Familiar with analysis via linear models preferably in R. If you don't have a statistical background or you lack experience with R you can follow these courses first: 

- Statistical thinking

- Basic statistics in R

- Basic statistics in R, part II

- Experimental Design


Joris De Wolf

Joris De Wolf has a long track record in biostatistics. He worked at Crop-Design, later BASF, as team leader of the biostatistics group. He was involved in the experimental design and start-up of the high-throughput phenotyping system TraitMill, design of the databases and streamlining of statistical analyses. Furthermore, he was research responsible for the field testing pipeline and statistics on transgenic yield improvement. In 2016, he joined GSK vaccines and currently he also works as a biostatistics consultant. 


Refresher on the important principles of experimental design and linear models

Factorial experiments: their place in research, advantages and disadvantages, screening and optimising experiments

Design and analysis of small factorial experiments

Fractions of factorial experiments

Optimal design in R

Analysis of complex factorial experiments and solving complex research question in R

Practical info

Location & Venue

14 December 2020 - 15 December 2020

Park Inn by Radisson Leuven

Martelarenlaan 36
3010 Leuven

Public transport

14 December 2020 - 15 December 2020

Park Inn by Radisson Leuven
Public transport

The hotel is located 300m from Leuven Central Station. The hotel connects to Leuven Central Station by a pedestrian bridge.

Route description

14 December 2020 - 15 December 2020

Park Inn by Radisson Leuven

Park Inn hotel has no own parking. It is possible to park underground in P1-Parking Station Leuven, Martelarenlaan 4, 3010 Leuven.

Venue contact

14 December 2020 - 15 December 2020

Park Inn by Radisson Leuven
Location contact

+32 16 61 66 02