In the past a number of car makers produced a wide range of classic cars that continue to increase in value. The following data, based upon the Martin Rating System for Collectible Cars, show the rarity rating (1 - 20) and the highest sales price ($1000s) for 15 Classic cars.
In the past a number of car makers produced a wide range of classic cars that continue to increase in value. The following data, based upon the Martin Rating System for Collectible Cars, show the rarity rating (1 - 20) and the highest sales price ($1000s) for 15 Classic cars.
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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In the past a number of car makers produced a wide range of classic cars that continue to increase in value. The following data, based upon the Martin
5 Rating System for Collectible Cars, show the rarity rating (1- 20) and the highest sales price ($1000s) for 15 Classic cars.
E
F
G
H
J
K
L
N
Q
R
4
6
7
Model Year
Make
Model
Rating
Price ($1000s)
8
1984
Chevrolet
18
1600
1956
Chevrolet
19
4000
10
1963
Chevrolet
18
1000
11
1978
Chevrolet
19
1300
12
1963
Ferrari
16
350
13
1964
Ferrari
19
2650
14
1962
Ferrari
18
375
15
1968
Ferrari
17
450
16
1973
Ferrari
17
140
17
1967
Jaguar
15
77.5
18
1971
Jaguar
14
62
Jaguar
Jaguar
19
1974
16
125
20
1954
17
400
21
1953
Jaguar
16
250
22
1967
Jaguar
13
70
23
24
A. Develop a scatter diagram of the data using rarity rating as the independent variable and price as the dependent variable. Does the
simple linear regression model appear to be appropriate ? Explain your Answer.
25
26
B. Develp an estimated multiple regresssion equation with x = rarity and x as the two independent variables.
27
1. What is your regression equation ?
28
2. What are this equations R² and Adjusted R2 statistics ?
29
3. What are your significance values for the entire equation and for the two independent varaibles ?
30
4. Plot the standardized residual values vs y*. Does it show that the distribution of the standardized residuals
31
fit the assumption of a normal distribution?
C. Develop a linear regression equation using logrithmic functions and fully evaluate the quality of that regression equation.
32
1. What is your regression equation ?
22
33
34
2. What are this equations R and Adjusted R* statistics ?
35
3. What are your significance values for the entire equation and for the two independent varaibles ?
36
4. Plot the standardized residual values vs y*. Does it show that the distribution of the standardized residuals
O 4)
37
fit the assumption of a normal distribution?
38
D. Which model do you prefer ? Why ? What is the predicted price for a Martin Rating of 19 ? How did that compare to the mean
7:07 PM
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price of cars in the original sample that had a rating of 19?
3/11/2021
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