Design and Analysis of Experiments
Conducting cost-effective experiments based on good design principles is fundamental to many areas of scientific research. In this course participants will learn to use resources effectively and to plan well-designed experiments, so as to obtain clear results and a high degree of precision.
During the course the concepts and principles of good experimental design will be discussed, together with associated data analysis methods. Computer based practicals with a choice from GenStat, Minitab and Stata will be used to analyse data from different types of experiments. Emphasis is placed on interpretation of computer output to help answer questions posed by research objectives.
Scientists, researchers, psychologists and industrial experimenters who design their own experiments and/or analyse experimental data. Participants should be familiar with the analysis of variance (ANOVA).
Participants will gain intuition and confidence in the statistical aspects of sound experimental design and learn how to analyse data arising from a variety of different designs.
Principles of experimental design
Playing "TOMATO" - an experimental simulation game to illustrate design concepts
Making sensible treatment comparisons
Blocking and latin square designs
Dealing with unbalanced data structures
Dealing with data structures involving both grouping variables (factors) and quantitative (covariates)
Factorial treatment structures and their analysis
Designing experiments in incomplete blocks.
Practical work may be done in: Genstat, Minitab, Stata
Note: For practical work, participants must bring their own laptop with a fully licensed version of their chosen software.