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 results are noisy, underpowered, or ambiguous. This guide helps you avoid common mistakes and get experiments that actually move your work forward.

What you'll get here

• A practical orientation to what matters when designing an experiment.
• A link to a reusable pre-registration worksheet you can save and share.
• A short checklist for last-minute sanity checks before you run the first sample.
• A quick reproducibility risk assessment to spotlight weak points before the experiment begins.

How to use this resource

Start by reading the practical guide to learn the key choices that influence interpretability and reproducibility. Then open the Experiment Planning Template to capture a short pre-registered plan that includes your hypothesis, primary endpoint, planned sample size and analysis method. Use the Quick Checklist right before you run the first experiment and the Reproducibility Risk Assessment to quantify and discuss weak spots with collaborators.

Quick promise

Complete the planning template and the checklist before data collection begins. That single habit removes ambiguity, reduces post-hoc decisions, and makes your results easier to interpret and reproduce.

When you find yourself thinking, "We can decide analysis later," pause and capture a brief plan instead. It will save time and reduce rework.