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AI & ML · Probability for ML

Bayes' theorem

304 problems in this skill, each with a solver-verified answer key. Answers are checked the moment you submit — with a hint if you want one and a worked solution afterwards.

What the problems look like

A few statements from this skill. Answers, hints and worked solutions live in the practice session.

  1. Warm-up

    An email inbox contains 7575 emails, of which 2424 are spam and the remaining 5151 are legitimate. Of the 2424 spam emails, 77 contain the word "free"; of the 5151 legitimate emails, 1111 contain the word "free". An email containing the word "free" is chosen at random. Using Bayes' theorem, find the probability that it is spam. Give your answer as a fraction.

  2. Warm-up

    An email inbox contains 9090 emails, of which 2222 are spam and the remaining 6868 are legitimate. Of the 2222 spam emails, 1111 contain the word "free"; of the 6868 legitimate emails, 22 contain the word "free". An email containing the word "free" is chosen at random. Using Bayes' theorem, find the probability that it is spam. Give your answer as a fraction.

  3. Warm-up

    An email inbox contains 9090 emails, of which 2828 are spam and the remaining 6262 are legitimate. Of the 2828 spam emails, 1010 contain the word "free"; of the 6262 legitimate emails, 55 contain the word "free". An email containing the word "free" is chosen at random. Using Bayes' theorem, find the probability that it is spam. Give your answer as a fraction.

Problems shown under their original terms: Generated (template, solver-computed).

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