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probability

Expected value

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Taught in

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Required by

Local knowledge map

Local knowledge map

Bayes' theorem Binary logistic regression Chebyshev's inequality Choosing a discrete model Covariance Cross-entropy, as a comparison of two distributions Functions of a random variable Gaussian mixture models and the EM algorithm Gaussian processes Generative classifiers: LDA and QDA Independence Mean under a linear transformation Poisson as a limit of binomial Random walks Single-server queues Standard deviation and units Sums of independent variables The Gaussian-noise / squared-loss connection The Monty Hall problem The binomial distribution The computational formula for variance The continuous uniform distribution The exponential distribution The geometric distribution The indicator trick The multiplication rule The normal distribution The sample average as a random variable The sampling distribution of a variance, previewed Conditional expectation Conditional probability Expectation for a continuous variable Expected value of a function of X (LOTUS) Expected value: the long-run average interpretation Gambler's ruin Games of chance and expected winnings Linearity of expectation Probability vocabulary for ML: Bayes' theorem,… Surprise and entropy The Bernoulli distribution The Poisson distribution The discrete uniform distribution Variance, defined Expected value A distribution is a list of probabilities summing to 1 Binomial probability Conditional distributions Indicator random variables Odds and probability Permutations repeated objects Probability as area Random variables Counting permutations combinations

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Solid arrows are required prerequisites; dashed are recommended or helpful. Lower rows are more foundational. Click any box to jump to that concept.