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
Related questions
Question
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.
![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:
SUMMARY
OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.879
0.773
0.756
Standard Error
59
Observations
30
ANOVA
Significance F
2.03428E-09
df
SS
MS
2
324863
162431
46.0
Regression
27
95443
3535
Residual
29
420306
Total
Standard
Upper 95%
104.894
1 Stat
P-value
Lower 95%
Error
Coefficients
20.209
0.49
0.63
-64.476
41.273
Intercept
Land (acres)
House Size(sq ft)
0.00
103.113
466.398
88.527
3.22
284.755
0.106
0.197
0.022
6.86
0.00
0.151
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.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6f622088-e5ba-4c84-b044-5e4b68af7b7e%2F7b9e0e85-67c5-402b-b4b2-3a66d1d56bc1%2Fkqg9ahc_processed.jpeg&w=3840&q=75)
Transcribed Image Text: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:
SUMMARY
OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.879
0.773
0.756
Standard Error
59
Observations
30
ANOVA
Significance F
2.03428E-09
df
SS
MS
2
324863
162431
46.0
Regression
27
95443
3535
Residual
29
420306
Total
Standard
Upper 95%
104.894
1 Stat
P-value
Lower 95%
Error
Coefficients
20.209
0.49
0.63
-64.476
41.273
Intercept
Land (acres)
House Size(sq ft)
0.00
103.113
466.398
88.527
3.22
284.755
0.106
0.197
0.022
6.86
0.00
0.151
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.
![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.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.920
0.847
0.807
Standard Error
52.84
Observations
30
ANOVA
Significance F
2.57569E-08
SS
MS
Regression
356099
59350
21.3
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
0.028
3.60
0.00
0.043
0.158
0.101
-2.27
0.03
-2.394
-0.113
-1.253
0.551
Age
0.17
-4.912
26.291
10.690
7.542
1.42
Rooms
0.74
-31.942
44.499
6.279
18.476
0.34
Baths
0.35
-18.687
50.629
16.754
0.95
15.971
Garage](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6f622088-e5ba-4c84-b044-5e4b68af7b7e%2F7b9e0e85-67c5-402b-b4b2-3a66d1d56bc1%2F7d515bk_processed.jpeg&w=3840&q=75)
Transcribed Image Text: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.
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.920
0.847
0.807
Standard Error
52.84
Observations
30
ANOVA
Significance F
2.57569E-08
SS
MS
Regression
356099
59350
21.3
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
0.028
3.60
0.00
0.043
0.158
0.101
-2.27
0.03
-2.394
-0.113
-1.253
0.551
Age
0.17
-4.912
26.291
10.690
7.542
1.42
Rooms
0.74
-31.942
44.499
6.279
18.476
0.34
Baths
0.35
-18.687
50.629
16.754
0.95
15.971
Garage
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