EBK STATISTICS FOR BUSINESS & ECONOMICS
EBK STATISTICS FOR BUSINESS & ECONOMICS
13th Edition
ISBN: 8220101456380
Author: Anderson
Publisher: CENGAGE L
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Chapter 16.4, Problem 19E
To determine

Construct an estimated multiple regression equation to predict the risk of a person.

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Spring is a peak time for selling houses. The file SpringHouses contains the selling price, number of bathrooms, square footage, and number of bedrooms of 26 homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor.com website) Click on the datafile logo to reference the data. DATA file a. The Excel output for the estimated regression equation that can be used to predict the selling price given the number of bathrooms, square footage, and number of bedrooms in the house: SUMMARY OUTPUT Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression statistics Regression Residual Total Multiple R R Square ANOVA Adjusted R Square Standard Error Observations 0.7429 0.5519 0.4907 61948.6931 Regression statistics Regression Residual Total df Intercept Sq Ft Beds Lower 95% 0.9353 -145129.5298 Intercept Baths 0.9528 -49383.5243 0.0180 Sq Ft Beds 0.0326 Does the estimated regression equation provide a good fit to the data? Explain. Hint: If R is greater than 45%, the…
Imagine you are conducting a hedonics study using housing data to evaluate how much a hazardous waste accident effected housing values. Which of the following should not be included in your regression? How many bedrooms each house has. Proximity to the waste. The quality of the local school district. All of these variables should be included.
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EBK STATISTICS FOR BUSINESS & ECONOMICS

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