A hands-on guide to experimental design covering variables, controls, sampling, randomization, power, pre-registration, and clear success criteria.
Welcome — Design experiments so the answers you get are useful. Designing an experiment is more than picking a control and counting measurements. A well-designed experiment turns curiosity into clear, reproducible evidence you can act on — quickly and with confidence. Teams that rush into testing often discover their...
Practical guide: Designing experiments that produce interpretable, reproducible results. Good experimental design makes the difference between a result that teaches you something and a result that wastes resources. This guide focuses on the decisions that most often determine whether an experiment is interpretable and...
Thinking about sample size: a practical guide (what decisions matter). Sample-size calculations often feel like a math exam. In practice, they are a device for making trade-offs explicit. This guide helps you turn uncertainty, cost, and decision impact into a defensible sampling plan. Start with the decision not the...
Concise, practical guidance and worked examples to choose sample sizes for common laboratory and computational studies. Covers core concepts (effect size, alpha, power, variability), simple heuristics, worked calculations for t-tests, ANOVA, and proportions, and pragmatic tips for pilots, adaptive designs, and reporting.