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experiment-design

Design robust experiments to test product hypotheses. Define metrics, sample size, and success criteria.

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Experiment Design

Design robust experiments to test product hypotheses.

When to Use

When you have a hypothesis and need to design an experiment to validate it.

The Process

1. Factor Breakdown

Analyze your goal and system:

  • What factors could influence the outcome?
  • Which are controllable vs. environmental?
  • What are the key variables?

2. Experiment Structure

For each factor, define:

  • Hypothesis: What you expect to happen
  • Independent variable: What you're changing
  • Dependent variable: What you're measuring
  • Control group: Baseline comparison
  • Experimental group: Who gets the change
  • Measurement method: How you'll collect data
  • Confounding variables: What else could affect results

3. Sample Design

  • Who participates?
  • How many needed for statistical significance?
  • How will you recruit/select?

4. Timeline

  • How long to run?
  • When to check results?
  • What's the minimum detectable effect?

5. Stop/Scale Rules

  • What results mean "stop"?
  • What results mean "scale"?
  • What's inconclusive?

Output Format

For each experiment:

  • Hypothesis statement
  • Variables (independent, dependent)
  • Groups (control, experimental)
  • Sample size and selection
  • Measurement approach
  • Success criteria
  • Stop/scale rules

When Not to Use

Do not use this skill when the request is unrelated, low-stakes, or better handled by a simpler direct response.

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