Learn fundamental concepts of probability and statistics through a comprehensive lecture covering expectations for both discrete and continuous random variables, with detailed examples using Bernoulli, Geometric, Exponential, and Normal distributions. Master the linearity of expectation principle while working through practical examples and derivations, including special focus on geometric decay, infinite sums, and the properties of normal distribution.
Probability and Statistics: Expectation of Random Variables - Lecture 8
Overview
Syllabus
Introduction
Discrete Random Variables
Example
Geometric Decay
Infinite Sum
Question
Derivation
Normal Distribution
Taught by
UofU Data Science
