Experimental Design
Overview
This one-day course is designed to complement training in statistical analysis, and focuses on how to design effective experiments while bearing in mind the planned analysis.
Included topics:
- Setting a good research question
- Choosing & defining variables
- Confounding variables
- Independence & pseudoreplication
- Revisiting statistical power
- Case study examples, for discussion
Learning Objectives
- Feel confident designing experiments with statistical analysis in mind
- Understand common “pitfalls” that occur when designing experiments, and how to avoid or combat them
- Apply these skills to at least one case study example
Prerequisites
Knowledge of core statistical concepts, including the statistical inference framework, linear modelling and power analysis, are required for the course. We recommend that students have attended the Core Statistics course or an equivalent.
Some of the course materials have been created using R; users may wish to follow along by copying the code themselves. If so, knowledge of statistical analysis in R is preferred.