Phase 2 · Math, when you need it · Probability & statistics
The normal distribution
The bell curve, and why it shows up everywhere.
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Why it matters
The bell curve is everywhere in statistics and machine learning: measurement noise, the spread of averages (which is why A/B tests work), the random numbers used to initialize every neural network's weights. Knowing its two parameters and a couple of rules of thumb lets you look at a number and immediately say "that's ordinary" or "that's three standard deviations out, something happened".
What you'll be able to do
- Describe the normal distribution by its mean and standard deviation
- Use the 68–95–99.7 rule and z-scores to judge how unusual a value is
- Compute normal probabilities and percentiles with SciPy
- Explain why sums and averages of many effects end up normal
Before this lesson
Next in this phase: Samples and confidence