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This interactive course is for MSD postgraduate research students and early career researchers wanting to understand the issues underpinning good experimental design, the bedrock of reproducible science.

You are required to attend on two dates:

  • Wednesday, 12 June, 14:00 - 16:30
  • Thursday, 13 June, 14:00 - 16:30


This course addresses some of the fundamental issues behind designing good experiments (focusing on pre-clinical experiments exclusively), the bedrock of reproducible science. Arguably, all good experiments start with a good experimental design.

Experimental design in the Biomedical Sciences is mostly about logic, common sense and the systematic application of relatively simple techniques to produce unbiased experimental results and reduce variation. This is good news because this should be relatively straightforward. Yet this is where the biggest blunders continue to be made, including by experienced biologists, with demonstrably expensive consequences on results.

The course will deal with those concepts, their links with statistical analyses generally and some of the traps that we have all fallen into. We will also address statistical issues relevant to animal research depending on the composition of the audience, in a session where the words “enjoyment” “experimental design” and “statistics” can hopefully share the same sentence. 

The sessions will be led by Manuel Berdoy, They will be interactive and the content will depend somewhat on the composition and needs of the group. You may have some tasks to carry out between the two live sessions.

Please make sure you read all of the sections below relating to how the course will work, and the survey and attendance certificate policy.


At the end of the course, attendees should be able to:

  • Describe some of the factors affecting reproducibility and external validity, the possible causes of bias and ways of alleviating it
  • List the different types of formal experimental designs, and explain the concept of variability, its causes and methods of reducing it
  • Identify the experimental unit and recognise issues of non-independence (pseudo-replication)
  • Describe the six factors affecting significance, including the meaning of statistical power and “p-values”
  • Identify formal ways of determining sample size
  • Explain the fundamental principles behind the output of an ANOVA, including “blocking” and “interactions”


Maximum 40


You will need to access the Canvas materials via the Canvas enrolment invitation sent out to you and make sure you go through the materials in advance of the live sessions to be able to fully participate in the course. The link will be shared one week before the course.


It is now a requirement that you complete the three short questions in the survey you receive after attending the course. Once you have submitted the survey, you will be sent an email with a link to your attendance certificate. This is to ensure we receive the feedback we need to evaluate and improve our courses. Survey results are downloaded and stored anonymously.