Probability Distributions: Basics

Related lectures (28)

Page 3 of 3

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.

Covers fundamental concepts of probability and statistics, focusing on data analysis, graphical representation, and practical applications.

Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

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

Covers fundamental concepts in probability and statistics, emphasizing data analysis techniques and statistical modeling.

Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.