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Related lectures (31)

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Transformations of Random Variables

Covers the pdf of the sum of continuous random variables, convolution, and transformations like Y=aX.

Probability and Statistics

Covers probability, statistics, independence, covariance, correlation, and random variables.

Stochastic Models for Communications

Covers random vectors, joint probability density, independent random variables, functions of two random variables, and Gaussian random variables.

Probabilistic Analysis: The Hiring Problem

Explores the probabilistic analysis of the hiring problem, focusing on strategies, expected hires, and randomized algorithms.

Stochastic Models for Communications

Explores stochastic models for communications, covering mean, variance, characteristic functions, inequalities, various discrete and continuous random variables, and properties of different distributions.

Quantifying Randomness in Biological Data

Covers randomness and information in biological data, focusing on discrete random variables and their quantification.

Statistical Theory: Fundamentals

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

Random Variables and Information Theory Concepts

Introduces random variables and their significance in information theory, covering concepts like expected value and Shannon's entropy.

Continuous Random Variables

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

Convergence of Random Variables

Explores independent and identically distributed random variables, convergence, and distribution properties.