experimental-design

experimental-design is an Experimentation & statistics skill for AI agents, published by K-Dense-AI in the scientific-agent-skills repository on GitHub. Skillspace rates experimental-design C (74/100) and it passed the safety scan; a judge model has also reviewed it.

Design experiments and studies BEFORE data is collected — choosing a design, randomizing, blocking, and laying out treatment combinations so results are interpretable. Use whenever someone is planning a study, asks how to assign subjects/samples to groups, mentions randomization, blocking, stratification, controls, factorial or fractional-factorial designs, design of experiments (DOE), screening many factors, response-surface optimization, crossover or repeated-measures or split-plot designs, cluster/group randomization, Latin squares, plate layouts, batch/run-order effects, replication vs. pseudoreplication, or sequential/adaptive/group-sequential designs. Trigger even for informal phrasings like "how should I set up this experiment", "how do I avoid confounding", "what's the best way to test these 6 factors", or "assign these mice to conditions". For computing the sample size or power once the design is chosen, use statistical-power; for analyzing data already collected, use…

Grade

C

Quality

74 / 100

Safety

Passed

GitHub stars

44,723

Placed #1 of 6 in the judged category final for Experimentation & statistics.

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