The data below contains mileage, age, and selling price for a sample of 33 sedans. Price Mileage Age 16,998 35,000 17,599 16,000 15,998 42,000 15,998 62,000 11,599 102,000 12,998 109,000 14,998 60,000 3 3 3 4 7 5 11,599 88,000 9 12,599 58,000 14,998 27,000 15,998 32,000 8 6 3 Price Mileage Age 11,599 95,000 11,499 123,000 8 14,599 54,000 10,599 68,000 12 16,998 40,000 20,998 80,000 11,599 12,599 70,000 13,599 86,000 92,000 11,599 8 7,000 5 4 0 9 6 5 7 9,599 120,000 10 Price 18,998 12,599 63,000 12,599 10,998 11,998 11,998 17,599 Mileage Age 9,998 20,000 70,000 86,000 60,000 88,000 10 45.000 95,000 9,998 16,998 36,000 2 7 17,599 45,000 6 6 6 2 60,000 11 11 2 2 (a) Develop an estimated regression equation that predicts the selling price of a used Honda Accord given the mileage and age of the car. (Round your numerical values to two decimal places. Let x, represent mileage, x₂ represent age, and y represent the selling prio ý – 20087.1– 0.04x1 – 642.15x, (b) Is multicollinearity an issue for this model? Find the correlation between the independent variables to answer this question.(Round your answer to two decimal places.)
The data below contains mileage, age, and selling price for a sample of 33 sedans. Price Mileage Age 16,998 35,000 17,599 16,000 15,998 42,000 15,998 62,000 11,599 102,000 12,998 109,000 14,998 60,000 3 3 3 4 7 5 11,599 88,000 9 12,599 58,000 14,998 27,000 15,998 32,000 8 6 3 Price Mileage Age 11,599 95,000 11,499 123,000 8 14,599 54,000 10,599 68,000 12 16,998 40,000 20,998 80,000 11,599 12,599 70,000 13,599 86,000 92,000 11,599 8 7,000 5 4 0 9 6 5 7 9,599 120,000 10 Price 18,998 12,599 63,000 12,599 10,998 11,998 11,998 17,599 Mileage Age 9,998 20,000 70,000 86,000 60,000 88,000 10 45.000 95,000 9,998 16,998 36,000 2 7 17,599 45,000 6 6 6 2 60,000 11 11 2 2 (a) Develop an estimated regression equation that predicts the selling price of a used Honda Accord given the mileage and age of the car. (Round your numerical values to two decimal places. Let x, represent mileage, x₂ represent age, and y represent the selling prio ý – 20087.1– 0.04x1 – 642.15x, (b) Is multicollinearity an issue for this model? Find the correlation between the independent variables to answer this question.(Round your answer to two decimal places.)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
Transcribed Image Text:The data below contains mileage, age, and selling price for a sample of 33 sedans.
Price Mileage Age
16,998 35,000
17,599 16,000
15,998 42,000
15,998 62,000
14,998 60,000
11,599 88,000
12,599
11,599 102,000
12,998 109,000 4
58,000
14,998 27,000
3
15,998 32,000
3
3
4
7
5
9
8
6
3
Mileage Age
11,599 95,000
11,499 123,000
Price
14,599 54,000
10,599
16,998 40,000
20,998
11,599
9,599
7,000
12,599 70,000
68,000 12
80,000
13,599 86,000
11,599 92,000
120,000
.
8
8
5
4
0
9
6
5
7
10
Price Mileage Age
18,998
12,599
12,599
10,998
11,998
11,998
17,599
20,000
63,000
70,000
86,000
60,000
88,000 10
45,000
9,998 60,000
2
16,998 36,000
7
17,599 45,000
6
6
9,998 95,000 11
6
2
11
2
2
(a) Develop an estimated regression equation that predicts the selling price of a used Honda Accord given the mileage and age of the car. (Round your numerical values to two decimal places. Let x₁ represent mileage, x₂ represent age, and y represent the selling price.)
y=20087.1 -0.04x₁ - 642.15x2
(b) Is multicollinearity an issue for this model? Find the correlation between the independent variables to answer this question. (Round your answer to two decimal places.)
The correlation between age and mileage is
Since this is <✔✔✔ 0.70, we conclude that multicollinearity is not
an issue.
✓
Expert Solution
Step 1
Given data:
| Price | Mileage | Age |
| 16998 | 35000 | 3 |
| 17599 | 16000 | 3 |
| 15998 | 42000 | 3 |
| 15998 | 62000 | 4 |
| 11599 | 102000 | 7 |
| 12998 | 109000 | 4 |
| 14998 | 60000 | 5 |
| 11599 | 88000 | 9 |
| 12599 | 58000 | 8 |
| 14998 | 27000 | 6 |
| 15998 | 32000 | 3 |
| 11599 | 95000 | 8 |
| 11499 | 123000 | 8 |
| 14599 | 54000 | 5 |
| 10599 | 68000 | 12 |
| 16998 | 40000 | 4 |
| 20998 | 7000 | 0 |
| 11599 | 80000 | 9 |
| 12599 | 70000 | 6 |
| 13599 | 86000 | 5 |
| 11599 | 92000 | 7 |
| 9599 | 120000 | 10 |
| 18998 | 20000 | 2 |
| 12599 | 63000 | 7 |
| 12599 | 70000 | 6 |
| 10998 | 88000 | 10 |
| 11998 | 86000 | 6 |
| 11998 | 60000 | 6 |
| 17599 | 45000 | 2 |
| 9998 | 95000 | 11 |
| 9998 | 60000 | 11 |
| 16998 | 36000 | 2 |
| 17599 | 45000 | 2 |
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