Topic · in development — big ideas below
Probability & statistics
Honest reasoning under uncertainty.
You can't know whether the coin lands heads — but you can know exactly how often it will in the long run. Probability quantifies uncertainty; statistics reads evidence backwards from data to truth. Together they're the mathematics of not being fooled.
The big ideas
Randomness has structure
A single die roll is unpredictable; a million rolls are astonishingly predictable. Probability is the study of that long-run order.
The normal curve keeps showing up
Add up many small independent influences — measurement errors, genetics, luck — and a bell curve emerges, almost no matter what. That's the central limit theorem, and it's why the bell is everywhere.
Evidence is a comparison
Data never proves alone — it shifts belief between competing explanations. “How surprising would this result be if nothing real were happening?” is the question behind every honest study.
Out in the world
Medical trials
Whether a drug works is a statistics question — separating real effect from lucky samples.
A/B testing
Every product decision backed by an experiment runs on hypothesis testing.
Insurance & risk
Premiums are expected values; the entire industry is applied probability.
The planned course
- 01Thinking in probabilitiesOdds, chance, and the rules of combining them.soon
- 02DistributionsThe shapes randomness takes.soon
- 03Mean, spread & the bell curveSummarizing data without lying.soon
- 04Sampling & confidenceHow much can a small sample really say?soon
- 05Hypothesis testingSurprise, evidence, and p-values — demystified.soon
- 06Bayes' ruleUpdating beliefs like a rational detective.soon
While you wait — this connects to material that's live now