Just parts d,e anf f of question 1 d) We conduct a simple regression of size on hhinc, now using robust standard errors. The regression output is reported in Table 2. Why are the estimated coefficients in Table 2 equal to the estimated coefficients in Table 1? Do the conclusions on the statistical significance at 5% of the coefficient of hhinc change between Tables 1 and 2? e) Now, using both the critical value and the p-value, test whether the coefficient of hhinc is statistically significant at 1%, by using the results in Table 1. Repeat the test by using the results in Table 2. Compare the results based on Table 1 with the results based on Table 2. Consider the results in Table 2. Compute the 99% confidence interval for hhinc. f) Consider the results in Table 2.How would you decide whether 0 is contained in the 99% confidence interval for the coefficient of hhinc, without actually computing the confidence interval?
Just parts d,e anf f of question 1 d) We conduct a simple regression of size on hhinc, now using robust standard errors. The regression output is reported in Table 2. Why are the estimated coefficients in Table 2 equal to the estimated coefficients in Table 1? Do the conclusions on the statistical significance at 5% of the coefficient of hhinc change between Tables 1 and 2? e) Now, using both the critical value and the p-value, test whether the coefficient of hhinc is statistically significant at 1%, by using the results in Table 1. Repeat the test by using the results in Table 2. Compare the results based on Table 1 with the results based on Table 2. Consider the results in Table 2. Compute the 99% confidence interval for hhinc. f) Consider the results in Table 2.How would you decide whether 0 is contained in the 99% confidence interval for the coefficient of hhinc, without actually computing the confidence interval?
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- Just parts d,e anf f of question 1
d) We conduct a simple regression of size on hhinc, now using robust standard errors. The regression output is reported in Table 2. Why are the estimated coefficients in Table 2 equal to the estimated coefficients in Table 1? Do the conclusions on the statistical significance at 5% of the coefficient of hhinc change between Tables 1 and 2?
e) Now, using both the critical value and the p-value, test whether the coefficient of hhinc is statistically significant at 1%, by using the results in Table 1. Repeat the test by using the results in Table 2. Compare the results based on Table 1 with the results based on Table 2. Consider the results in Table 2. Compute the 99% confidence interval for hhinc.
f) Consider the results in Table 2.How would you decide whether 0 is contained in the 99% confidence interval for the coefficient of hhinc, without actually computing the confidence interval?
![Table 1
regress size hhinc
Source
SS
df
MS
Number of obs
5,407
F(1, 5405)
1613.34
Model
263141566
1
263141566
Prob > F
0.0000
Residual
R-squared
=
Adj R-squared
%3D
Total
1.1447e+09
5,406
211749.457
Root MSE
%3D
size
Coefficient
Std. err.
P>|t|
[95% conf. interval]
hhinc
.0082545
.0002055
40.17
0.000
.0078516
.0086574
_cons
800.9835
9.404917
85.17
0.000
782.5461
819.4209
c) Compute the Sum of Squared Residuals (SSR), R-squared (R^2), and Root Mean
Squared Error from Table 1 (Root MSE). Interpret the R-squared.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F00af739a-4010-4669-9e5e-5bc99db6959f%2F46af89a7-b71f-41fd-bda2-784c86e8b899%2F7qdcccv_processed.png&w=3840&q=75)
Transcribed Image Text:Table 1
regress size hhinc
Source
SS
df
MS
Number of obs
5,407
F(1, 5405)
1613.34
Model
263141566
1
263141566
Prob > F
0.0000
Residual
R-squared
=
Adj R-squared
%3D
Total
1.1447e+09
5,406
211749.457
Root MSE
%3D
size
Coefficient
Std. err.
P>|t|
[95% conf. interval]
hhinc
.0082545
.0002055
40.17
0.000
.0078516
.0086574
_cons
800.9835
9.404917
85.17
0.000
782.5461
819.4209
c) Compute the Sum of Squared Residuals (SSR), R-squared (R^2), and Root Mean
Squared Error from Table 1 (Root MSE). Interpret the R-squared.
![Table 2
• regress size hhinc, robust
Linear regression
Number of obs
5,407
F(1, 5405)
134.25
%3D
Prob > F
0.0000
%3D
R-squared
0.2299
Root MSE
403.86
Robust
size
Coefficient
std. err.
P>|t|
[95% conf. interval]
hhinc
.0082545
.0007124
11.59
_cons
800.9835
25.72644
31.13
e) Now, using both the critical value and the p-value, test whether the coefficient of
hhinc is statistically significant at 1%, by using the results in Table 1. Repeat the test
by using the results in Table 2. Compare the results based on Table 1 with the results
based on Table 2.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F00af739a-4010-4669-9e5e-5bc99db6959f%2F46af89a7-b71f-41fd-bda2-784c86e8b899%2Fu0fdhin_processed.png&w=3840&q=75)
Transcribed Image Text:Table 2
• regress size hhinc, robust
Linear regression
Number of obs
5,407
F(1, 5405)
134.25
%3D
Prob > F
0.0000
%3D
R-squared
0.2299
Root MSE
403.86
Robust
size
Coefficient
std. err.
P>|t|
[95% conf. interval]
hhinc
.0082545
.0007124
11.59
_cons
800.9835
25.72644
31.13
e) Now, using both the critical value and the p-value, test whether the coefficient of
hhinc is statistically significant at 1%, by using the results in Table 1. Repeat the test
by using the results in Table 2. Compare the results based on Table 1 with the results
based on Table 2.
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