Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Discrete Random Variables: Functions and Probabilities
Graph Chatbot
Related lectures (37)
Probability and Statistics
Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.
Advanced Probabilities: Random Variables & Expected Values
Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.
Random Variables and Expected Value
Introduces random variables, probability distributions, and expected values through practical examples.
Random Variables: Expected Value
Covers advanced probability concepts, including random variables and expected value calculation.
Continuous Random Variables
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Probability and Statistics: Fundamental Theorems
Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.
Probability and Statistics
Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.
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.
Random Variables: Basics and Examples
Explains random variables, distributions, and Bernoulli trials with coin flip examples.
Conditional Probability Distributions
Covers conditional probability distributions and introduces the concept of conditional expected value.
Random Variables: Expectation and Independence
Explores random variables, expectation, and independence in probability theory.
Probability and Statistics: Independence and Conditional Probability
Explores independence and conditional probability in probability and statistics, with examples illustrating the concepts and practical applications.
Probability and Statistics: Fundamentals
Log in to Mediaspace to watch this video
Covers the fundamental concepts of probability and statistics, including interesting results, standard model, image processing, probability spaces, and statistical testing.
Probability and Statistics
Log in to Mediaspace to watch this video
Explores joint random variables, conditional density, and independence in probability and statistics.
Elements of Statistics: Probability and Random Variables
Log in to Mediaspace to watch this video
Introduces key concepts in probability and random variables, covering statistics, distributions, and covariance.
Statistical Theory: Fundamentals
Log in to Mediaspace to watch this video
Covers the basics of statistical theory, including probability models, random variables, and sampling distributions.
Introduction to Inference
Log in to Mediaspace to watch this video
Covers the basics of probability theory, random variables, joint probability, and inference.
Previous
Page 1 of 2
Next