Statistics 101 lecture outline: Continuous random variables

Statistics 101: Continuous random variables

Uniform Random Variables (a,b)
- Where Uniform Random Variables Come From and Parameters
- Main Result: f(y) and F(y) and Computing Probabilities with an Example
- Mean and Variance and Example
Exponential Random Variables (lambda)
- Physical Process and Parameter (Relation to Poisson)
- Results for f(y) and F(y) and Example
- Reason for Result and Another Example
- Results for Mean and Variance with Examples
- Application to Longevity and the Notion of Memoryless
Introduction to Normal Random Variables
- Physical Process
- Examples
- Discussion of Parameters
Results for Normal Random Variables
- Motivate Desired Results with an Example
- Description of the Normal Density Function
- Standard Normal Random Variable and its Properities
- Computing Probabilities for Normal Random Variables with Examples
- Computing Quantiles for Normal Random Variables with Examples
last updated: $Date: 2006-04-05 17:38:25 -0400 (Wed, 05 Apr 2006) $