Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Covers continuous random variables, probability density functions, and distributions, with practical examples.
Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.
Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.
Covers the Central Limit Theorem and its application to random variables, proving convergence to a normal distribution.
Explores stochastic models for communications, covering mean, variance, characteristic functions, inequalities, various discrete and continuous random variables, and properties of different distributions.
