lecture5solutions

# lecture5solutions - ISYE 6414 - Spring 2009 Solution...

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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 ....
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## 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.

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lecture5solutions - ISYE 6414 - Spring 2009 Solution...

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