Expectation and Variance

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (29)

Page 3 of 3

Advanced Probabilities: Random Variables & Expected Values

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

Probability Theory: Midterm Solutions

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

Estimating R: Moments of a Distribution

Explains the importance of moments in measuring distribution properties, such as expectation and variance.

Probability and Stochastic Processes: Fundamentals and Applications

Discusses the fundamentals of probability and stochastic processes, focusing on random variables, their properties, and applications in statistical signal processing.

Probability and Statistics

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Introduction to Inference

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

Conditional Density and Expectation

Covers conditional density, independence of random variables, expectation, and variance calculation.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Statistical Theory: Fundamentals

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