Discrete Random Variables: Functions and Probabilities

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (30)

Page 2 of 3

Statistical Theory: Fundamentals

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

Probability Theory: Midterm Solutions

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

Probability and Statistics

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

Calculations of Expectation

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

Expectation of a Random Variable

Defines the expectation for random variables, emphasizing the importance of absolute values.

Introduction to Inference

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

Conditional Density and Expectation

Explores conditional density, expectations, and independence of random variables with practical examples.

Random Variables: Basics and Examples

Explains random variables, distributions, and Bernoulli trials with coin flip examples.

Normal Distribution: Properties and Calculations

Covers the normal distribution, including its properties and calculations.

Probability and Random Variables: Key Concepts Explained

Explains key concepts in probability, including conditional probability, independence, and random variables, with practical examples to illustrate their applications.