# 2-2-09 - a Definitions – a Sample Mean b Sample Variance...

This preview shows pages 1–6. Sign up to view the full content.

Economic Statistics – Class Notes – 2/2/09 From exercise on 1/30/09: Average = standard For FRIDAY (everything we did on 1/28/09 and 1/30/09): Proof for Rules of Expectation (#1-6) o These are all based on summation Direct Applications o Know the examples of these direct applications Standardizing a random variable and showing that the expectation of “Z” = 0 and that the variance of Z = 1 Expected value and variance of functions of random variables: o E(X + Y) etc.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
Example – Rules of Expectation: Direct Application versus Proof USING THE PROOF:
7. The Covariance and the Correlation Coefficient

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: a.) Definitions – a. Sample Mean: b. Sample Variance: c. Sample Covariance: Examples of related variables: • Height and Weight • Education levels and incomes o More education = more income • GDP and consumption • Investment and interest rate The sample covariance is used to estimate the population variance: Question: How does the sample covariance determine whether a direct, indirect, or no relation exists between the random variable X and the random variable Y? Answer: QUIZ FRIDAY!...
View Full Document

## This note was uploaded on 06/03/2009 for the course ECON 203 taught by Professor Casler during the Spring '09 term at Allegheny.

### Page1 / 6

2-2-09 - a Definitions – a Sample Mean b Sample Variance...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online