A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Using data collected for a sample of n = 91 houses in East Meadow, the appraiser fit the data with the following simple, linear regression model: y 91.80 + 19.72x, where x = number of rooms and y = appraised value of the house (in thousands of dollars). Additionally, the appraiser determined the coefficient of correlation to be r=.93 and the coefficient of determination to be r = 86. Give a practical interpretation of the slope of the least squares line.

A county real estate appraiser wants to develop a statistical model to predict the appraised value of houses in a section of the county called East Meadow. One of the many variables thought to be an important predictor of appraised value is the number of rooms in the house. Using data collected for a sample of n = 91 houses in East Meadow, the appraiser fit the data with the following simple, linear regression model: y 91.80 + 19.72x, where x = number of rooms and y = appraised value of the house (in thousands of dollars). Additionally, the appraiser determined the coefficient of correlation to be r=.93 and the coefficient of determination to be r = 86. Give a practical interpretation of the slope of the least squares line.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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