Learning Tracks

Learn the concept, then practise it against a real company. Five of these are full courses whose lessons run in order, built on real companies' published numbers and studies, with interactive simulations wherever the true answer has to be known for a method to be scored rather than asserted. Start with Probability & Statistics if the foundations are shaky; the other four assume them. The Concept Crash Course is a library rather than a course: one article per concept, read whichever one a question sends you to. The case bank is where you go once you know what you are looking at.

Product Analytics

Define a metric properly, then use it to work out what moved and why, with examples from real companies' published numbers.

21 lessons

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Experimentation

Design an A/B test, size it, and read it without fooling yourself. Twenty lessons built on experiments that real companies have published.

20 lessons

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Advanced Experimentation

The experiment questions that separate a senior candidate from a competent one. Bayesian readouts, bandits, designs that buy precision, and measuring what a two-week test cannot see.

10 lessons

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Causal Inference

Measure an effect when you cannot randomise. Twenty-two lessons built on real studies, with interactive simulations where the true answer is known.

22 lessons

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Probability & Statistics

The machinery every other track leans on. Twenty-five lessons built on real data, from the US jobs report to Student's 1908 sleep study, with simulations wherever the truth needs to be known.

25 lessons

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Concept Crash Course

The standalone explainers. One concept per article, reachable from any practice answer that leans on it, in no particular order.

6 articles

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Product Sense & Metrics

The case bank. One deep guide per company product: its users, its money, its metrics.

47 companies

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