1 distributions of two random variables 42 the

Info iconThis preview shows page 1. Sign up to view the full content.

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

Unformatted text preview: Culpepper, SA STAT 400: Statistics and Probability I (7) Discrete Definitions Discrete Examples Continuous Definitions Continuous Examples 4.1: Distributions of two random variables 4.2: The Correlation Coefficient Continuous Examples: P (X > Y ) 1. One easy approach, 1−y 0.5 x 2 ydxdy = P (X > Y ) = 60 0 y 11 16 (8) 2. Still an easier approach, 1−x 0.5 x 2 ydydx = 1 − P (X > Y ) = 1 − 60 0 x 11 5 = (9) 16 16 3. The more cumbersome approach, 0.5 x 0 = 1−x 1 x 2 ydydx + 60 P (X > Y ) = 60 0 x 2 ydydx 0.5 0 3 8 11 + = 16 16 16 Culpepper, SA (10) STAT 400: Statistics and Probability I Definitions Examples Predictions, Best Fit Line 4.1: Distributions of two random variables 4.2: The Correlation Coefficient Example Bivariate Plot 6 q q q 5 Non−Smokers Smokers q Lung Capacity (l3) q 4 q q q 3 2 q 1 q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q q...
View Full Document

This note was uploaded on 12/12/2013 for the course STAT 400 taught by Professor Kim during the Fall '08 term at University of Illinois, Urbana Champaign.

Ask a homework question - tutors are online