For Educators · Central Limit Theorem
Central Limit Theorem for a dice-fairness check
Built for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs. Simulate a dice-fairness check live below — adjust the inputs and watch it respond, right in your browser.
Central Limit TheoremLive
means go normal
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The central limit theorem is why the normal distribution is everywhere: no matter how skewed or lumpy the source distribution, the distribution of sample means becomes bell-shaped as the sample size grows. Try a heavily skewed exponential at n=1, then raise n and watch it turn normal.
Data Inspector
Samples drawn0
Sample size10
Sourceexponential
Governing equation
Reading this result: At n=10 the sample means are already piling into a bell even though the exponential source is not normal — the central limit theorem kicking in.
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Frequently asked questions
- Is this good for educators?
- Yes — this version of "Central Limit Theorem for a dice-fairness check" is framed for educators teaching it to a class. Drop a live demo into a lecture or assign it as a shareable link — no lab installs.
- Do I need to install anything?
- No. It runs in any modern browser, free, with no account required.