Probability and Statistics: Discrete Random Variables

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Covers the fundamentals of probability theory, including corollaries, conditional probability, total probability theorem, and random variables.

Explores continuous random variables, density functions, and distribution laws with practical examples.

Covers conditional probability distributions and introduces the concept of conditional expected value.

Covers conditional density, independence of random variables, expectation, and variance calculation.

Introduces fundamental probability concepts, including events, complements, conditional probability, and random variables.

Explores discrete and continuous random variables, independence, and probability functions.

Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.

Introduces random variables, probability distributions, and expected values through practical examples.

Covers fundamental concepts in probability and statistics, including the law of total probability, Bayes' theorem, and independence of events.