What makes it an experiment
Two ways to investigate
- An observational study measures things as they are, without interfering — you watch and record.
- An experiment does something: you apply a treatment to some units and compare them with units that did not get it.
- Only a well-designed experiment can support a claim of cause and effect.
The variables
- The explanatory variable (the treatment) is the thing you change or apply — e.g. giving a fertiliser, or not.
- The response variable is what you measure to see the effect — e.g. the mass of tomatoes per plant.
- The experimental units are the things the treatment is applied to — the plants, the people, the plots.
Why an experiment can show cause, but an observation cannot
- In an observational study, the groups you compare may differ in other ways too — these are confounding variables.
- Example: if sunnier plants happened to be the ones that got fertiliser, you could not tell whether fertiliser or sunshine caused a bigger yield.
- An experiment removes this problem by using random allocation: units are split into groups by chance, so other factors are balanced out across the groups on average.
Treatment and control
- The treatment group receives the treatment.
- The control group does not — it is the baseline you compare against.
- Because allocation was random, the only systematic difference between the groups is the treatment, so a difference in the response can be attributed to the treatment.
A grower wants to know whether a new fertiliser increases tomato yield. She takes 24 similar plants, randomly assigns 12 to get the fertiliser and 12 to get none, and later weighs the tomatoes from each plant. Identify the experimental units, the explanatory variable, the response variable, and why this is an experiment.
Step 1 — Units
The experimental units are the 24 tomato plants.
Step 2 — Explanatory (treatment) variable
Whether a plant gets the fertiliser or not — this is what the grower controls.
Step 3 — Response variable
The mass of tomatoes per plant — what is measured to see the effect.
Step 4 — Why it is an experiment
The grower applies a treatment (fertiliser) and randomly allocates plants to the two groups, so it is an experiment — and any yield difference can be linked to the fertiliser rather than to some other factor.
Test yourself
Practice by grade
One question each at Achieved, Merit and Excellence. Have a go, then compare with the model answer.
A researcher randomly gives half of 40 volunteers a caffeine drink and half a caffeine-free drink, then measures their reaction times. State the explanatory variable and the response variable.
Explain why the caffeine study is an experiment and not an observational study, and why that matters for the conclusion.
A newspaper reports that people who drink coffee have faster reaction times, based on surveying coffee drinkers and non-drinkers. Explain why this cannot show that coffee causes faster reactions, and how an experiment would fix it.