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Experimental Design Fundamentals

Interactive experimental-design simulator: split subjects into control and treatment groups, tune sample size, effect size, noise and randomization to see when a measured difference is real evidence versus a confound.

Data Science3DModerate60 FPS

Good experiments separate a real effect from ordinary noise and hidden bias. This simulator visualizes a simple two-group trial: subjects are split into a control group and a treatment group, each subject's outcome is its baseline plus random variation plus (for the treatment group) the true effect being tested, and the two group means are compared. Adjust sample size to see replication tame randomness, dial the true effect and noise to see when a difference becomes detectable, and turn off randomization to watch an unrelated confound masquerade as a real effect — the core reason controlled, randomized, replicated trials produce trustworthy results.

⚙ Under the hood

Interactive control-vs-treatment trial simulator: tune sample size, true effect size, noise and randomization to see when a measured difference is real evidence versus a confound.

Three.jsexperimental-designstatisticsrandomizationcontrol-groupdata-science

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install