mcs3500 a2

.pdf

School

University of Guelph *

*We aren’t endorsed by this school

Course

3500

Subject

Marketing

Date

Apr 3, 2024

Type

pdf

Pages

8

Uploaded by CorporalDragonflyMaster637

Marketing Analytics M C S 3500 _S ec. 2 ( Winter 2023) Assignment 2: Market Response Model (100 Points) Due on March 03 (by mid - night) Data: boston housing. csv randomly sample only 406 house prices from 50 6 house prices. For all questions , use log( medv ) as outcome or dependent variable ( see data description in next page ) Multiple Linear Regression (50 points ) : Q 1 (A).
Identify most important variables using best subset algorithm to predict house prices using three model selection criteria ( RSS = residual sum of square; adjr^2 = adjusted R^2 and BIC =Bayesian information criteria). 20 points Q 1 (B). Develop a conceptual framework using important variables identified in Q 1 (A ). Also, provide descriptive statistics for the identified important variables in Q 1 (A) . (5 + 5 = 10 points ) Q 1 (C). Run multiple linear regression model with these identified variables in Q 1 (A) . Write regression equation and i nterpret any four regression coefficients.
20 points Multiple Linear Regression with Quadratic Effects (30 points ) : Q 2 (A). Run multiple regression analysis with the variables identified in Q 1 (A) with adding quadratic effects of average numbers of rooms ( rm ) and provide average marginal effects (ame) with comments. 10 points Q 2 (B). Plot and interpret prediction and average marginal effects of average number of rooms ( rm ) . 20 points Multivariate Adaptive Splines (MARS) (20 points ) : Q 3 (A). Run MARS using all variables in the housing data to investigate non - linear response patterns. Comments on your findings
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
  • Access to all documents
  • Unlimited textbook solutions
  • 24/7 expert homework help