Summary
Randomisation, replication, blocking and blinding reduce bias and confounding.
In depth
Elements: randomisation, replication, controls, blocking, blinding and counterbalancing. Pseudoreplication (treating non-independent samples as independent) is a common error. Randomised controlled trials are the gold standard in medicine.
Plan analysis before collecting data. Pilot studies test feasibility. Randomise order to avoid time effects.
Example: randomised block designs control for field gradients.
Frequently asked questions
What is Experimental Design?
Randomisation, replication, blocking and blinding reduce bias and confounding.
Which area of biology covers Experimental Design, and how advanced is it?
Experimental Design is one of the 51 topics in Lab Methods & Biostatistics. It is rated Advanced, so it suits learners who want specialist depth. Related topics in this area include Statistical Power, Variables, P-Values and Multiple Testing.
Can you give an example of Experimental Design?
Split-plot designs in agriculture.
What should I learn before Experimental Design?
Work through the Beginner topics in Lab Methods & Biostatistics first, such as Scientific Method, Hypothesis, Variables, then return to Experimental Design. Advanced topics assume the Intermediate vocabulary.
What topics are related to Experimental Design?
The closest topics to Experimental Design are Statistical Power, Variables, P-Values and Multiple Testing, Control Group. Comparing them side by side is a good way to see how the ideas connect.
How can I check that I understand Experimental Design?
Read the summary and the in-depth section, then use the quick check on the interactive lesson for Experimental Design. To practise the whole of Lab Methods & Biostatistics, use the Lab Methods & Biostatistics quiz.
How is Experimental Design different from Statistical Power?
Experimental Design: Randomisation, replication, blocking and blinding reduce bias and confounding. Statistical Power: The probability of detecting a true effect, determined by sample size, effect size and variability. Read both side by side and note what each one explains.
How should I study Experimental Design step by step?
First, read the summary and write the definition in your own words. Second, read the in-depth section and note any example. Third, compare it with Statistical Power and explain the difference aloud. Finally, take the Lab Methods & Biostatistics quiz and come back to this page for any question you miss.