This preview shows pages 1–2. 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: 1ECON2P91: Review Questions No. 2 1. Textbook Chapter 4 Page 137 q. 4.1 (a) The predicted average test score is 520 4 5 82 22 392 36 TestScore = .  . = . (b)The predicted change in the classroom average test score is ( 5 82 19) ( 5 82 23) 23 28 TestScore =  .   . = . (c) Using the formula for in Equation (4.8), we know the sample average of the test scores across the 100 classrooms is 1 520 4 5 82 21 4 395 85 TestScore CS = + = .  . . = . . (d)Use the formula for the standard error of the regression (SER) in Equation (4.19) to get the sum of squared residuals: 2 2 ( 2) (100 2) 11 5 12961 SSR n SER = = . = . Use the formula for 2 R in Equation (4.16) to get the total sum of squares: 2 2 12961 13044 1 1 0 08 SSR TSS R = = = . . The sample variance is 2 Y s = TSS 13044 1 99 131 8. n = = . Thus, standard deviation is 2 11 5. Y Y s s = = . 2. Textbook Chapter 4 Page 137 q. 4.2 The sample size 200. n = The estimated regression equation is 2 (2 15) 99 41 (0 31) 3 94 0 81 SER 10 2 Weight Height R = . . + . . , = . , = . . (a) Substituting 70, 65, and 74 Height = inches into the equation, the predicted weights are 176.39, 156.69, and 192.15 pounds. (b) 3 94 3 94 1 5 5 91. Weight Height = . = . . = . (c) We have the following relations: 1 2 54 and 1 0 4536 . in cm lb kg = . = . Suppose the regression equation in the centimeterkilogram space is 1 Weight Height = + ....
View
Full
Document
This note was uploaded on 04/28/2011 for the course ECON 2P91 taught by Professor Ogwang during the Winter '09 term at Brock University, Canada.
 Winter '09
 Ogwang
 Econometrics

Click to edit the document details