6) The following results are from data that were collected from the appraisal of houses based on a number of the houses' characteristics: the dependent variable is APPRAISAL VALUE, the variable Land measures the amount of land the lot is, HOUSE SIZE measures the size of the house, AGE measures how old the house is, RO OMS measures the number of bedrooms the house has, BATHS measures the number of bathrooms a house has, and GARAGE measures weather it is a 1 or 2 car garage. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.920 0.847 0.807 Standard Error 52.84 Observations 30 ANOVA df SS MS F Significance F Regression 356099 59350 21.3 2.57569E-08 Residual 23 64206 2792 Total 29 420306 Upper 95% 225.364 Standard Error t Stat P-value Lower 95% Coefficients 83.064 68.789 1.21 0.24 -59.236 Intercept Land (acres) House Size(sq ft) 80.883 3.61 0.00 124.865 459.504 292.184 3.60 0.00 0.043 0,158 0.101 0.028 -2.27 0.03 -2.394 -0.113 -1.253 0.551 Age 0.17 -4.912 26.291 7.542 1.42 10.690 6.279 Rooms 0.74 -31.942 44.499 18.476 0.34 Baths -18.687 50.629 16.754 0.95 0.35 Garage 15.971
6) The following results are from data that were collected from the appraisal of houses based on a number of the houses' characteristics: the dependent variable is APPRAISAL VALUE, the variable Land measures the amount of land the lot is, HOUSE SIZE measures the size of the house, AGE measures how old the house is, RO OMS measures the number of bedrooms the house has, BATHS measures the number of bathrooms a house has, and GARAGE measures weather it is a 1 or 2 car garage. SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.920 0.847 0.807 Standard Error 52.84 Observations 30 ANOVA df SS MS F Significance F Regression 356099 59350 21.3 2.57569E-08 Residual 23 64206 2792 Total 29 420306 Upper 95% 225.364 Standard Error t Stat P-value Lower 95% Coefficients 83.064 68.789 1.21 0.24 -59.236 Intercept Land (acres) House Size(sq ft) 80.883 3.61 0.00 124.865 459.504 292.184 3.60 0.00 0.043 0,158 0.101 0.028 -2.27 0.03 -2.394 -0.113 -1.253 0.551 Age 0.17 -4.912 26.291 7.542 1.42 10.690 6.279 Rooms 0.74 -31.942 44.499 18.476 0.34 Baths -18.687 50.629 16.754 0.95 0.35 Garage 15.971
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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6) The following results are from data that were collected from the appraisal of houses based on a number of the houses’ characteristics: the dependent variable is APPRAISAL VALUE, the variable Land measures the amount of land the lot is, HOUSE SIZE measures the size of the house, AGE measures how old the house is, ROOMS measures the number of bedrooms the house has, BATHS measures the number of bathrooms a house has, and GARAGE measures weather it is a 1 or 2 car garage.
*see below*
Since the 3 variables ROOMS, BATHS, and GARAGE are each not significant at the 10% level of significance individually, in order to test to see if as a group they are significant (versus the alternative that they are not significant and that house values are really determined primarily by LAND, HOUSE SIZE, and AGE) the 3 variables are excluded and another regression is run. The results are as follows:
*see below*
a) At the 10% level of significance, test whether as a group ROOMS, BATHS, and GARAGE are significant. Be sure to state the null and alternative hypothesis for this hypothesis test.
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