Experimental Design Specialist

Designs rigorous experiments — from clinical RCTs to A/B tests to industrial DOE — with proper randomization, power analysis, control structures, and statistical validity to produce actionable causal evidence.

Gold

v1.0.00 activationsData & AnalyticsTechnologyadvanced

SupaScore

83.8

Research Quality (15%)

8.5

Prompt Engineering (25%)

8.3

Practical Utility (15%)

8.5

Completeness (10%)

8.2

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.5

Best for

▸A/B testing sample size calculation for 2% conversion rate improvement detection
▸Clinical trial randomization strategy for multi-center drug efficacy study
▸Industrial DOE factorial design for optimizing manufacturing process parameters
▸Power analysis for behavioral intervention studies in education settings
▸Stratified randomization design for marketplace seller experiments

What you'll get

●Detailed experimental protocol with 12-step methodology, power calculations showing 2,640 users needed per group, stratified randomization by user tenure, and pre-specified analysis plan
●Industrial DOE specification with 2^4 factorial design, blocking strategy for batch effects, response surface methodology recommendations, and statistical analysis framework
●Clinical trial design with CONSORT-compliant protocol, adaptive randomization algorithm, interim analysis plan, and ethical consideration framework

Not designed for ↓

×Data analysis of completed experiments (that's post-experiment analysis)
×Statistical modeling or machine learning algorithm selection
×Survey design for market research (needs survey design specialist)
×Observational study design without experimental intervention

Expects

Clear research question, target population, expected effect size, and practical constraints like budget, timeline, and randomization unit definition.

Returns

Complete experimental design specification including randomization method, sample size calculations, control structures, and validity threat mitigation strategies.

Evidence Policy

Enabled: this skill cites sources and distinguishes evidence from opinion.

experimental-designa-b-testingrctdoepower-analysisrandomizationfactorial-designsample-sizecausal-inferencestatistical-methodstaguchiclinical-trials

Research Foundation: 8 sources (3 books, 2 academic, 1 official docs, 1 paper, 1 industry frameworks)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/16/2026

Initial release

Works well with

A/B Test AnalystPlatinum Bayesian A/B Testing ExpertGold Causal Inference AnalystGold Hypothesis Testing ExpertGold Statistical Analysis AdvisorPlatinum

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Monte Carlo Simulation ExpertGold Bayesian Statistics ExpertPlatinum

Common Workflows

Complete A/B Testing Pipeline

Design rigorous experiment, analyze results, and establish causal conclusions with proper statistical inference

experimental-design-specialist→A/B Test Analyst→Causal Inference Analyst

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