Section 1 — Controls
✓ What you will learn
- Why small samples look noisy and big samples look stable.
- How simulation (computer trials) slowly matches theory (math truth).
- The core idea behind ML: more data usually reduces randomness errors.
Start with coin. Dice will show the same idea with 6 bars.
Try 50 first, then 5000. You will *see* the difference.
7000 trials/sec
Seed helps debugging: same seed ⇒ same result pattern.
Section 2 — Live Readings
🎯 What you will learn
- How to read a probability chart: bars = “what we saw”, dashed line = “what math expects”.
- What “error” means in simple words: “how far we are from the truth”.
Completed Trials
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Max Error (how far from theory)
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Mean Error (average distance)
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Coach Explanation
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Tip: Start with 50 trials. Then do 5000 trials and compare.
Section 3 — Histogram (Animated)
Blue bars = what the computer observed
Yellow dashed line = what math expects
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Live sentence (kid-friendly)
Press Start to begin.