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
Probability Distributions: Moments and Transformations
Graph Chatbot
Related lectures (39)
Advanced Probabilities: Random Variables & Expected Values
Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.
Probabilities and Statistics: Key Theorems and Applications
Discusses key statistical concepts, including sampling dangers, inequalities, and the Central Limit Theorem, with practical examples and applications.
Statistics: Random Variables and Probability Density Functions
Introduces random variables, probability density functions, and Gaussian distribution in statistics.
Continuous Random Variables
Explores continuous random variables, density functions, joint variables, independence, and conditional densities.
Introduction to Continuous Random Variables: Probability Distributions
Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.
Continuous Random Variables
Covers continuous random variables, probability density functions, and distributions, with practical examples.
Generating Functions: Properties and Applications
Explores generating functions, Laplace transform, and their role in probability distributions.
Calculations of Expectation
Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.
Fundamental Limits of Gradient-Based Learning
Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.
Probability and Statistics
Covers probability distributions, moments, and continuous random variables.
Probability Theory: Midterm Solutions
Covers the solutions to the midterm exam of a Probability Theory course, including calculations of probabilities and expectations.
Continuous Random Variables: Basic Ideas
Explores continuous random variables and their properties, including support and cumulative distribution functions.
Normal Distribution: Properties and Calculations
Covers properties and calculations related to the normal distribution, including probabilities and quantiles.
Model Specification: The Error Term
MOOC: Introduction to Discrete Choice Models
Delves into the binary choice model, error term specification, and Extreme Value distribution properties.
Probability and Statistics: Fundamental Theorems
Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.
Convergence of Random Variables
Explores different modes of convergence for random variables.
Advanced Probability: Summary
Covers random variables, sample spaces, probability distributions, functions, expected value, variance, and estimations.
Statistical Inference: Random Variables
Covers random variables, probability functions, expectations, variances, and joint distributions.
Probability Distributions: Basics and Properties
Log in to Mediaspace to watch this video
Covers the basics of probability distributions, including mean, variance, and properties of random variables.
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.
Previous
Page 1 of 2
Next