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• Is it better to have more treatments or more replicates?
• How do I choose the treatment for each experimental unit?
• What is the best layout for the trial in the field or laboratory?
• How many experimental units (what sample size) do I need?

Target participants

Students and researchers who are interested in the statistical issues in experimental design and the analysis of data from designed experiments or studies with several factors.

Course content

• Developing specific objectives for a study within a broad research project;
• The basic principles of experimental design: randomisation, replication, blocking and  local control;
• Advantages of factorial treatment designs;
• Randomisation as the basis for the analysis;
• Common designs: completely randomised, randomised complete block, split plot experiments;
• Organising data into a form suitable for analysis using a statistics package;
• Hypothesis testing via the analysis of variance table;
• Estimation of means and standard errors;
• Interpretation of output from a statistics package used for analysing one of the above designs.

Assumed Knowledge

It is assumed that course participants have completed Introductory Statistics Online or equivalent and so have familiarity with:

• The concept of variation;
• Graphical methods for displaying the distribution of data;
• Confidence for a mean;
• Interpreting the P-value from a hypothesis test