SCIENCE · INVESTIGATE AND EXPLAIN

Choose controls and independent repetitions

Distinguish a useful control from a repeated biased comparison.

Learning outcome: Explain what matching controls and replication can each identify.

Starting recap

A repeated measurement on one unit is not a newly assigned experimental unit.

All lessons are open directly. Your saved experiments remain when you leave and return.

Try

A training program is compared with a class that began at a different level.

Open the experiment

Predict

Will repeating the same unequal group composition remove its confounding?

Your prediction and reason

Experiment

Capture an unequal comparison twice, then capture an equal-composition comparison. Explain which change matters.

Repair a group comparison

Worked teaching model · synthetic values · High-baseline outcomes are 80 points; low-baseline outcomes are 40. The programmed treatment adds 4 in both strata. No noise or unmeasured confounder is included.

High-baseline share in treatment group: 80 % High-baseline share in comparison group: 20 %

Reset keeps your prediction, captures and practice history.

Calculated values on the same fixed scale
Row	Quantity	Value (points)
1	Treatment mean	76
2	Comparison mean	48
3	High stratum treatment	84
4	High stratum comparison	80
5	Low stratum treatment	44
6	Low stratum comparison	40

Headline difference: 28.0 points. Within each stratum: 4 points.

Treatment mean = 84 × treated high share + 44 × treated low share. The headline gap equals 4 + 40 × (treated high share − comparison high share). Matching composition repairs this particular bias, not every possible confounder.

Observation to attach to a capture

Captures preserve recipes and replay their calculated results. They are synthetic model evidence, not physical measurements.

Understand

A control needs to answer the same question

The treatment and comparison should differ in the intended intervention while other relevant influences are controlled or accounted for. The lab’s baseline composition is one influence. Matching it lets you inspect the programmed treatment difference.

Repeating the exact same settings reproduces the same calculation. It is not a new trial and cannot average away composition bias. This deterministic replay is useful for checking arithmetic, not estimating natural variability.

Name the experimental unit

If one plant is measured ten times, there is one plant and ten readings. If ten plants receive independently assigned conditions, the investigation can examine between-plant variation. Treating repeated readings as ten independent plants exaggerates the evidence.

Pairing can compare similar units, but order and carryover can still matter. For example, trying method A before B may teach a participant the task. A paired design needs an order plan as well as a pair definition.

Write the outcome before seeing results. “Find whichever score improved most” is different from testing a predeclared primary outcome.

Use your captures to separate three ideas: replaying a calculation, obtaining another independent unit, and repairing a systematic design difference. Your procedure should state which one it actually performs.

Apply

Public practice checks a specific claim. It does not establish independent mastery.

Propose independent assignment or pairing, one remaining threat, and an outcome specified in advance.

Your explanation and limitations

Continue

Completion requires a saved prediction, at least one capture and a reflection. Presence checks do not grade your reasoning.

Skipping retains experiments and awards no mastery.

Previous: Repair an unfair comparison Next: Inspect who entered the sample

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