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Design experiments using control, randomization, replication, and blocking.
Learn step-by-step with practice exercises built right in.
Random Assignment
Control Group
Blinding
Placebo Effect
Blocking
An experiment tests whether adding fertilizer increases tomato plant yield. All 60 plants are kept in the same greenhouse at the same temperature, watered equally, but half receive fertilizer and half don't. Why is this good experimental design?
Why this design is strong:
Random Assignment: The 60 plants are randomly divided into two groups (30 fertilized, 30 not), ensuring the groups are comparable before treatment.
Control of Variables: All other factors are held constant — same greenhouse, temperature, water, light, soil type. This eliminates confounding variables so differences in yield come from fertilizer, not other causes.
Avoid these 3 frequent errors
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Matched Pairs Design
Replication
Can you randomly assign? → Experiment (can infer causation) Cannot randomly assign? → Observational (report association only)
"Design an experiment" prompts require: statement of hypotheses, identification of variables, treatment groups, control group, blinding method, randomization procedure, outcome measurement, and conclusion.
Control Group: The unfertilized group serves as a baseline to compare against; without it, we wouldn't know if the treated group's yield is high.
Replication: Using 60 plants instead of 1 or 2 gives multiple observations, reducing the effect of individual plant variation and increasing reliability.
Result: If fertilized plants significantly outyield unfertilized ones, we can confidently conclude fertilizer causes higher yield because confounding factors were controlled.
A researcher wants to compare three new cancer drugs on 150 patients. Suggest a design that uses blocking and explain why blocking improves the experiment.
Design with Blocking:
Block by disease stage (three blocks):
Within each block, randomly assign 1/3 to Drug A, 1/3 to Drug B, 1/3 to Drug C (so ~17 per group per block).
Response: Measure survival time or remission rate after 12 months.
Why blocking improves the experiment:
Disease stage is a confounding variable — late-stage patients naturally have different outcomes than early-stage regardless of drug. Without blocking, if by chance more late-stage patients got Drug A, its apparent effectiveness would be artificially lowered (confounded with stage).
Blocking isolates the drug effect from stage effect by ensuring each block (stage level) has equal numbers on each drug. We can then:
This increases precision and makes differences between drugs clearer.
Design a double-blind experiment testing whether a memory supplement improves test performance. Explain what 'double-blind' means and why both levels of blinding are essential.
Study Design:
Participants: 100 college students
Groups:
Random Assignment: Students randomly assigned to supplement or placebo
Blinding:
Implementation: A neutral third party prepares identical-looking pills, labels them only with code numbers. After the study, codes are revealed.
Response: Test performance measured 8 weeks after starting pills
Why double-blinding is essential:
Eliminates placebo effect (student level): If students knew they got the real supplement, improved performance might come from psychological expectation, not the pill itself. Blinding ensures any improvement is physiological.
Eliminates experimenter bias (researcher level): If researchers knew who had supplements, they might unconsciously encourage supplement students differently, treat them with more enthusiasm, or score their tests more leniently. Blinding prevents this.
Result: Any difference in performance between groups is reliably caused by the supplement, not expectations or bias.
Without double-blinding, results are unreliable — we can't tell if the supplement or expectations caused improvement.