Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Probability Distributions: Discrete and Continuous
Graph Chatbot
Related lectures (29)
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.
Dependence and Correlation
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
Transformations of Joint Densities
Covers the transformations of joint continuous densities and their implications on probability distributions.
Introduction to Continuous Random Variables: Probability Distributions
Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.
Introduction to Inference
Covers the basics of probability theory, random variables, joint probability, and inference.
Random Variables and Expected Value
Introduces random variables, probability distributions, and expected values through practical examples.
Linear Regression: Theory and Applications
Covers the theory and practical applications of linear regression.
Convergence in Probability
Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.
Probability and Statistics
Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.
Previous
Page 2 of 2
Next