The following results are from data where the dependent variable is EXPENSE FEES, the independent variables are SAFETY RATING, PERFORMANCE, and LOAD which is a dummy variable = 1 for load funds and = 0 for no-load funds. d) What is the standard error of the error term in the regression equation? e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above?
The following results are from data where the dependent variable is EXPENSE FEES, the independent variables are SAFETY RATING, PERFORMANCE, and LOAD which is a dummy variable = 1 for load funds and = 0 for no-load funds. d) What is the standard error of the error term in the regression equation? e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above?
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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6) The following results are from data where the dependent variable is EXPENSE FEES, the independent variables are SAFETY RATING, PERFORMANCE, and LOAD which is a dummy variable = 1 for load funds and = 0 for no-load funds.
d) What is the standard error of the error term in the regression equation?
e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?
f) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above?
Transcribed Image Text:6) The following results are from data where the dependent variable is EXPENSE FEES, the independent
variables are SAFETY RATING, PERFORMANCE, and LOAD which is a dummy variable =1 for
load funds and = 0 for no-load funds.
Complete the results:
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
20
ANOVA
df
SS
MS
F
Significance F
Regression
0.7694
0.0087
Residual
Total
19
1.517
Coefficients
Standard Error
t Stat
P-value
Upper 95%
Lower 95%
Intercept
1.391
2.025
0.687
0.502
-2.901
5.683
Safety Rating
-0.0338
0.2666
-0.1267
0.9008
-0.5990
0.5315
Performance (%)
0.0069
0.0035
0.0636
-0.0004
0.0142
Load
0.233
0.102
2.293
0.036
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