Discrete Random Variables: Functions and Probabilities

Related lectures (30)

Page 3 of 3

Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.

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

Explores random variables, expectation, and independence in probability theory.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.

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

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

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

Covers the basics of probability distributions, including mean, variance, and properties of random variables.

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