Experimental Design
Randomisation, control and blinding.
Key idea
Randomisation, control and blinding.
In depth
Good experiments use control groups, random assignment, blinding and replication to isolate cause. Randomisation balances unknown confounders. Observational studies cannot guarantee that.
Worked example
Randomly assign patients to a drug or placebo; compare outcomes.
Real-world uses
- Planning a clinical trial with random assignment and a placebo group
Common mistake
Assigning treatments by convenience or letting subjects choose.
How to learn this
- Read the key idea and say it in your own words.
- Work through the worked example, then try a similar problem.
- Use the interactive lesson’s visual and mini-quiz to check the pattern.
Frequently asked questions
What is Experimental Design?
Randomisation, control and blinding. It is a topic at the advanced level in Probability & Statistics.
Where is Experimental Design used in real life?
Real-world examples: Planning a clinical trial with random assignment and a placebo group.
What should I learn before Experimental Design?
Make sure you are comfortable with Time Series Basics, the previous topic in Probability & Statistics.
What is a common mistake with Experimental Design?
Assigning treatments by convenience or letting subjects choose.
How can I practise Experimental Design?
Open the interactive lesson, play with the visual, then answer the three-question mini-quiz. Getting two right marks the topic complete.
What comes after Experimental Design?
Move on to Data Ethics and Misleading Graphs next.
Related advanced topics in Probability & Statistics
- Quartiles and IQR – Quartiles split data into four parts; IQR = Q3 − Q1.
- Box Plots – Five-number summary visualised.
- Outliers – Values beyond 1.5 IQR from the quartiles.
- Variance – Average squared deviation from the mean.
- Standard Deviation – Square root of variance; typical spread.
- Sample vs Population Variance – Divide by n−1 for sample variance.