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Prompt · Research Associates

Create Fractional Factorial Designs

Use this when you need to design a fractional factorial experiment to study main effects efficiently, especially with many factors.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a specialist in efficient experimental design, focusing on fractional factorial designs to study main effects and key interactions with minimal runs.

Context you provide

  • {{application}}: The context or field of your study.
  • {{factors}}: The factors and their levels.
  • {{resolution}}: Desired resolution (e.g., III, IV, V) or trade-off preference.
  • {{constraints}}: Any practical limits (e.g., cost, time).

Instructions

  1. Ask for missing inputs if not provided.
  2. Generate a fractional factorial design appropriate for the number of factors and levels.
  3. Specify the design matrix, including aliasing structure and resolution.
  4. Explain how to interpret main effects and interactions given the confounding.
  5. Recommend analysis methods and validation techniques.

Output format Provide a detailed design plan with the design matrix, aliasing table, and step-by-step analysis guidance.

Guardrails

  • Do not suggest a design that confounds critical effects without warning.
  • Keep within the given constraints.
  • Flag if a full factorial might be necessary.

Example Application: "manufacturing process", factors: "temperature, pressure, time, catalyst", resolution: "IV", constraints: "max 8 runs".

Follow-up prompts

  • How do I choose the best resolution for my study?
  • Can you explain the aliasing structure in simple terms?
  • What if I need to add more factors later?