The owner of Maumee Ford Mercury Volvo wants to study the relationship between t
ID: 3315047 • Letter: T
Question
The owner of Maumee Ford Mercury Volvo wants to study the relationship between the age of a car and it's selling price.
of Maumee Ford Mercury-Volvo wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at the dealership during the last year Car Age (years) Seling Price (5000) Car Age (years) Selling Price (5000) 2 3 4. 5 6 8 16 18 9 8 12.2 11.0 4.9 4.1 6.7 13.6 10 16 14 18 6 6 11.1 9.0 9.0 4.2 12.1 10.4 8 9 10 12 Click here for the Excel Data File (a) Determine the regression equation. (Round your answers to 3 decimal places. Negative values should be indicated by a minus sign.) a F (b) Estimate the selling price of a 7-year-old car (in S000) (Round your answer to 3 decimal places.) Selling price (c) Interpret the regression equation (in dollars). (Round your answer to nearest dollar amount.) For each additional year, the car decreases S in valueExplanation / Answer
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.78
R Square
0.61
Adjusted R Square
0.57
Standard Error
2.17
Observations
12
ANOVA
df
SS
MS
F
Significance F
Regression
1
73.38
73.38
15.57
0.00
Residual
10
47.14
4.71
Total
11
120.52
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
15.69
1.80
8.71
0.00
11.68
19.71
Age (x)
-0.57
0.14
-3.95
0.00
-0.89
-0.25
Car
Age (x)
Selling Price (y)
x^2
y^2
xy
1
11
12.2
121
148.84
134.2
2
8
11
64
121
88
3
16
4.9
256
24.01
78.4
4
18
4.1
324
16.81
73.8
5
9
6.7
81
44.89
60.3
6
8
13.6
64
184.96
108.8
7
10
11.1
100
123.21
111
8
16
9
256
81
144
9
14
9
196
81
126
10
18
4.2
324
17.64
75.6
11
6
12.1
36
146.41
72.6
12
6
10.4
36
108.16
62.4
140
108.3
1858
1097.93
1135.1
a)
b1= nE(xy)-ExEy/nE(x2)-(Ex2)
=12*1135.1-(140*108.3)/12*1858-(140*140)
=-0.5715
b0=Ey-b1Ex/n
=108.3-(-0.5715*140)/12
=188.31/12
=15.6925
b)
y=15.6925-0.5715x
y=15.6925-0.5715*7
y=15.6925-4.0005
y=11.692
c)
$571.5 (0.5715*1000)
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.78
R Square
0.61
Adjusted R Square
0.57
Standard Error
2.17
Observations
12
ANOVA
df
SS
MS
F
Significance F
Regression
1
73.38
73.38
15.57
0.00
Residual
10
47.14
4.71
Total
11
120.52
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
15.69
1.80
8.71
0.00
11.68
19.71
Age (x)
-0.57
0.14
-3.95
0.00
-0.89
-0.25
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