ML Prep

Probability

Move from events and conditioning through moments, distributions, and asymptotic results.

Recommended resources

Instructions

  1. Name conditioning events and random variables explicitly.
  2. Check independence before factorizing.

Ordered items

  1. Counting, total probability, and independenceProbability · Easy · 7 min · Original
  2. Bayes rule and diagnostic evidenceProbability · Medium · 12 min · External
  3. Events, unions, and conditional probabilityProbability · Medium · 6 min · External
  4. Joint tables, Bayes rule, and independenceProbability · Medium · 14 min · External
  5. Recognize distribution momentsProbability · Easy · 8 min · Original
  6. Lognormal transformation by the CDF methodProbability · Medium · 12 min · External
  7. Diagnostic testing with base ratesProbability · Medium · 8 min · External
  8. Conditional expectation and total varianceProbability · Medium · 8 min · Original
  9. Linear transform of a multivariate GaussianProbability · Medium · 8 min · Original
  10. Joint density, moments, covariance, and correlationProbability · Hard · 24 min · External
  11. Central limit theorem for an aggregateProbability · Medium · 10 min · External
  12. LLN versus CLTProbability · Easy · 5 min · Original

Completion

Move fluently among event, distribution, expectation, and covariance representations.

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