Look at the example on slide 58 (page 107) of the course packet.
Assume you have conducted two regressions using the same data. The first
regression on the "full model" had 9 independent variables, and a sample size of
200. You then run a "reduced model" after eliminating 4 of the independent
variables that appeared insignificant on the basis of the individual ttests. Data for
the "full model": SSR=95,532 and MSE=645. Data for the "reduced model":
SSR=7,978 and MSE=13,431.
1.
The partial F statistic for this test is
33.93566 = 33.93566
.
2.
The pvalue for the above partial Ftest is
2.32758e21 = 2.32758e21
.
3.
What is your conclusion:
reject the null hypothesis and proceed with
using the full model
Now conduct the same test, this time assuming the SSR from your reduced
model is 92,300.
4.
The partial Fstat and the corresponding pvalue are respecively
1.2527
and
.2902 = 0.2902
5.
What is your conclusion:
fail to reject the null hypothesis and proceed
with using the reduced model
You received a raw score of 100% on this question.
Question #2
You worked as an intern at We Always Win Car Insurance Company last summer
and noticed that individual car insurance premiums depended very much on the age
of the individual, the number of traffic tickets received by the individual, whether
the car was a convertible and the population density of the city in which the
individual lived.
To see if your conjecture is correct, you got the following EXCEL
output
.
The pvalue for the partial Ftest when the "group" of variables you are testing is
made up of the variable DENSITY is:
0.174472482
The pvalue for the ttest of the individual slope coefficient for DENSITY is
0.174472482
1.
You received a raw score of 100% on this question.
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 Spring '08
 Petry
 Statistics, Regression Analysis, Profit margin, Statistical hypothesis testing

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