Lectures related to Probability and Statistics

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

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

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

Covers continuous random variables, probability density functions, and distributions, with practical examples.

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

Explores variance, covariance, and practical applications in statistics and probability.

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