The manager of a used-car dealership is very interested in the resale price of
used cars. The manager feels that the age of the car is important in determining
the resale value. He collects data on the age and resale value of 15 cars and
runs a regression analysis with the value of the car (in thousands of dollars) as
the dependent variable and the age of the car (in years) as the independent
variable. Unfortunately, the printout had lost some of the results, identified by
"
A
" through "
F
". The partial results left are displayed below.
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.442
R Square
"
A
"
Adjusted R Square
0.133
Standard Error
"
B
"
Observations
15.000
ANOVA
df
SS
MS
F
Significance
F
Regression
1
44.397
44.397
3.154
0.09914
Residual
13
"
C
"
14.076
Total
14
227.389
Coefficients
Standard
Error
t Stat
P-value
Intercept
"
D
"
3.835
5.988
0.000
Age
"
E
"
0.640
-1.776
"
F
"
