This preview shows pages 1–3. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: ISYE 6414  Spring 2009 Solution lecture 5 The Linear Model: Multiple Regression Problem 6.1 Pag.248 1. X = 1 X 11 X 11 X 12 1 X 21 X 21 X 22 1 X 31 X 31 X 32 1 X 41 X 41 X 42 T = ( , 1 , 2 ). 2. X = 1 X 11 X 12 1 X 21 X 22 1 X 31 X 32 1 X 41 X 42 T = ( , 1 , 2 ). Problem 6.2 Pag.248 1. X = 1 X 11 X 12 X 2 11 1 X 21 X 22 X 2 21 1 X 31 X 32 X 2 31 1 X 41 X 42 X 2 41 1 X 51 X 52 X 2 51 T = ( , 1 , 2 , 3 ). 2. X = 1 X 11 log 10 X 12 1 X 21 log 10 X 22 1 X 31 log 10 X 32 1 X 41 log 10 X 42 1 X 51 log 10 X 52 T = ( , 1 , 2 ). Problem 6.3 Pag.248 A good model should explain the response well with a small set of predic tors. Problem 6.4 Pag.248 Because r 12 measures the linear relation between Y and X , so its sign is the same as the slope sign. However, in the multiple correlation R , there are several variables. Problem 6.22 Pag.253 1. Yes 2. No. But making Y = log Y , the model is linear. Y i = + 1 X i 1 + 2 X 2 i 2 + i . Where i = log i . 1 3. Yes. Y i = 1 + log 10 X i 1 + 2 X i 2 + i ....
View
Full
Document
This note was uploaded on 09/01/2011 for the course ISYE 6414 taught by Professor Staff during the Fall '08 term at Georgia Institute of Technology.
 Fall '08
 Staff

Click to edit the document details