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
Transformations of Variables
Graph Chatbot
Related lectures (54)
Continuous Random Variables
Covers continuous random variables, probability density functions, and distributions, with practical examples.
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.
Linear Combinations: Moment-Generating Functions
Explores moment-generating functions, linear combinations, and normality of random variables.
Statistical Inference: Random Variables
Covers random variables, probability functions, expectations, variances, and joint distributions.
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.
Families of Distributions: PDFs and CDFs
Explores PDFs and CDFs for discrete and continuous random variables, including Gaussian, uniform, and exponential distributions.
Multivariate Statistics: Normal Distribution
Introduces multivariate statistics, covering normal distribution properties and characteristic functions.
Sampling Theory: Statistics for Mathematicians
Covers the theory of sampling, focusing on statistics for mathematicians.
Common Distributions: Moment Generating Functions
Explores common probability distributions, special distributions, and entropy concepts.
Statistical Models: Families and Transformations
Explores statistical models, families of distributions, transformations, and their applications in probability theory.
Generating Functions: Properties and Applications
Explores generating functions, Laplace transform, and their role in probability distributions.
Estimation and Confidence Intervals
Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.
Calculations of Expectation
Covers the calculation of expectation and variance for different types of random variables, including discrete and continuous ones.
Advanced Probabilities: Random Variables & Expected Values
Explores advanced probabilities, random variables, and expected values, with practical examples and quizzes to reinforce learning.
Continuous Random Variables: Basic Ideas
Explores continuous random variables and their properties, including support and cumulative distribution functions.
Probability and Statistics: Fundamental Theorems
Explores fundamental theorems in probability and statistics, joint probability laws, and marginal distributions.
Probability Distributions: Central Limit Theorem and Applications
Log in to Mediaspace to watch this video
Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.
Normal Distribution: Properties and Calculations
Log in to Mediaspace to watch this video
Covers the normal distribution, including its properties and calculations.
Normal Distribution: Basics and Applications
Log in to Mediaspace to watch this video
Covers the basics of the normal distribution and its applications in probability calculations.
Previous
Page 1 of 3
Next