7) The data used above was split into 2 samples and the following regression results were obtained from the split data. a) What is heteroscedasticity? b) Why is heteroscedasticity a problem? c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain. Be sure to write down your null and alternative hypothesis, calculate the test statistic, and find your critical value (use a 10% level of significance).
7) The data used above was split into 2 samples and the following regression results were obtained from the split data. a) What is heteroscedasticity? b) Why is heteroscedasticity a problem? c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain. Be sure to write down your null and alternative hypothesis, calculate the test statistic, and find your critical value (use a 10% level of significance).
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
7) The data used above was split into 2 samples and the following regression results were obtained from the split data.
a) What is heteroscedasticity?
b) Why is heteroscedasticity a problem?
c) Based on a comparison of the two sets of output, does it appear that there is heteroscedasticity in the data set? Explain. Be sure to write down your null and alternative hypothesis, calculate the test statistic, and find your critical value (use a 10% level of significance).
Transcribed Image Text:Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
0.950
0.902
0.818
48.5
Observations
14
ANOVA
SS
MS
Significance F
Regression
152083
25347
10.8
0.0031
Residual
16478
2354
Total
13
168561
Coefficients
-31.0
Standard Error
1 Stat
P-value
Lower 95%
-467.7
Upper 95%
Intercept
Land (acres)
House Size(sq ft)
Age
184.7
-0.2
0.9
405.6
278.9
90.0
3.1
0.0
66.2
491.6
0.089
0.035
2.537
0.039
0.006
0.171
-1.52
0.95
-3.76
-16.0
-1.61
0.15
0.71
Rooms
31.6
20.1
1.6
0.2
79.1
Baths
20.1
27.7
0.7
0.5
-45.4
85.6
Garage
13.5
33.3
0.4
0.7
-65.3
92.2
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
0.840
0.706
0.485
Standard Error
32.27
Observations
15
ANOVA
MS
Significance F
df
SS
F
19998
3333
3.201
0.066
Regression
Residual
8.
8331
1041
14
28330
Total
Upper 95%
276.2
Standard Error
t Stat
P-value
Lower 95%
Соеficients
155.0
52.6
2.9
0.0
33.8
Intercept
Land (acres)
House Size(sq ft)
348.4
-291.8
-0.035
28.3
138.8
0.2
0.8
0.183
0.155
0.041
1.456
0.060
-0.291
0.591
-1.489
0.907
0.520
-0.560
Age
1.3
0.2
-6.3
23.8
8.8
6.5
Rooms
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