Test 1: Multiple Linear Regression. Given the following data: y X₁ X₂ X3 X4 X5 8.0 19.6 94.9 2.3 5.2 29.6 x6 2.1 2.1 2.0 8.3 19.8 89.7 1.8 5.2 32.4 8.5 19.6 96.2 2.0 5.8 31.0 8.8 19.4 95.6 2.1 6.4 32.4 2.2 9.0 18.6 86.5 1.8 5.8 28.6 2.0 9.3 18.8 84.5 2.1 5.2 30.6 2.1 9.3 20.4 88.8 1.9 5.6 32.4 2.2 9.5 19.0 85.7 1.9 6.0 32.6 2.1 9.8 20.8 93.6 2.1 5.2 32.2 2.3 10.0 19.9 86.0 1.8 5.8 31.8 2.1 10.3 18.0 87.1 1.6 6.4 32.6 2.0 10.5 20.6 93.1 2.1 6.0 33.4 2.1 10.8 20.2 83.4 2.1 6.2 31.8 2.2 11.0 20.2 94.5 1.9 6.2 32.4 2.1 11.3 19.2 83.4 1.8 6.2 31.4 1.9 11.5 17.0 85.2 2.1 5.6 33.2 2.1 11.8 19,8 84.1 1.8 6.0 35.4 2.0 12.3 18.8 86.9 1.8 5.8 34.0 2.1 12.5 18.6 83.0 2.0 5.6 34.2 1.9 A. With x₁, x₂, X5 and x, as regressors, fit a multiple linear regression model to the given data. B. Suppose that the regressors are grouped as follows: -Group 1 (B₁): X₁, X4, X5 -Group 2 (B₂): x2, X3, X6 ادی 1010 INNO
Test 1: Multiple Linear Regression. Given the following data: y X₁ X₂ X3 X4 X5 8.0 19.6 94.9 2.3 5.2 29.6 x6 2.1 2.1 2.0 8.3 19.8 89.7 1.8 5.2 32.4 8.5 19.6 96.2 2.0 5.8 31.0 8.8 19.4 95.6 2.1 6.4 32.4 2.2 9.0 18.6 86.5 1.8 5.8 28.6 2.0 9.3 18.8 84.5 2.1 5.2 30.6 2.1 9.3 20.4 88.8 1.9 5.6 32.4 2.2 9.5 19.0 85.7 1.9 6.0 32.6 2.1 9.8 20.8 93.6 2.1 5.2 32.2 2.3 10.0 19.9 86.0 1.8 5.8 31.8 2.1 10.3 18.0 87.1 1.6 6.4 32.6 2.0 10.5 20.6 93.1 2.1 6.0 33.4 2.1 10.8 20.2 83.4 2.1 6.2 31.8 2.2 11.0 20.2 94.5 1.9 6.2 32.4 2.1 11.3 19.2 83.4 1.8 6.2 31.4 1.9 11.5 17.0 85.2 2.1 5.6 33.2 2.1 11.8 19,8 84.1 1.8 6.0 35.4 2.0 12.3 18.8 86.9 1.8 5.8 34.0 2.1 12.5 18.6 83.0 2.0 5.6 34.2 1.9 A. With x₁, x₂, X5 and x, as regressors, fit a multiple linear regression model to the given data. B. Suppose that the regressors are grouped as follows: -Group 1 (B₁): X₁, X4, X5 -Group 2 (B₂): x2, X3, X6 ادی 1010 INNO
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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Transcribed Image Text:Test 1: Multiple Linear Regression. Given the following data:
y
X₁
X₂
X3
X₁
X5
X6
8.0
19.6
94.9
2.3
5.2
29.6
2.1
8.3
19.8
89.7
1.8
5.2
32.4
2.1
8.5
19.6
96.2
2.0
5.8
31.0
2.0
8.8
19.4
95.6
2.1
6.4
32.4
2.2
9.0
18.6
86.5
1.8
5.8
28.6
2.0
9.3
18.8
84.5
2.1
5.2
30.6
2.1
9.3
20.4
88.8
1.9
5.6
32.4
2.2
9.5
19.0
85.7
1.9
6.0
32.6
2.1
9.8
20.8
93.6
2.1
5.2
32.2
2.3
10.0
19.9
86.0
1.8
5.8
31.8
2.1
10.3
18.0
87.1
1.6
6.4
32.6
2.0
10.5
20.6
93.1
2.1
6.0
33.4
2.1
10.8
20.2
83.4
2.1
6.2
31.8
2.2
11.0
20.2
94.5
1.9
6.2
32.4
2.1
11.3
19.2
83.4
1.8
6.2
31.4
1.9
11.5
17.0
85.2
2.1
5.6
33.2
2.1
11.8
19.8
84.1
1.8
6.0
35.4
2.0
12.3
18.8
86.9
1.8
5.8
34.0
2.1
12.5
18.6
83.0
2.0
5.6
34.2
1.9
A. With x₁, x₂, X5 and x, as regressors, fit a multiple linear regression model to the given data.
B. Suppose that the regressors are grouped as follows:
-Group 1 (B₁): X₁, X₁, X5
-Group 2 (B₂): X₂, X3, X6
Transcribed Image Text:Test
the significance of B₁ at a = 0.05.
C. From the model in (A), construct a normal probability plot of residuals (cumulative normal probability
or standard normal scores vs. residuals). What can you say from this plot?
D. What can you say about any influential observations in the data? Justify your answer numerically.
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