Probability Basics: Theory and Applications

Related lectures (29)

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Introduces key statistical concepts like probability, random variables, and correlation, with examples and explanations.

Explains conditional probability through dice and coin examples.

Covers the basics of probability theory, random variables, joint probability, and inference.

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

Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.

Covers discrete and continuous probability distributions, including joint and conditional probabilities.

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

Offers a review of key probability concepts, including probability spaces, events, and random variables.

Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.