Transformations of Variables

Related lectures (30)

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Covers properties and transformations of discrete random variables, focusing on PMF and expectation.

Covers the multivariate normal distribution, properties, and sampling methods.

Explores statistical models, families of distributions, transformations, and their applications in probability theory.

Explores generating functions, Laplace transform, and their role in probability distributions.

Covers the fundamentals of probability theory, including conditional probability, Bayes' rule, and random variables.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.

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

Explores continuous random variables and their properties, including support and cumulative distribution functions.

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