4.3 Consider the simple linear regression model fit to the solar energy data. DATA SETS FOR EXERCISES 555 TABLE B.2 Solar Thermal Energy Test Data y x₁ X₂ X3 X4 xs 271.8 783.35 33.53 40.55 16.66 13.20 264.0 748.45 36.50 36.19 16.46 14.11 238.8 684.45 34.66 37.31 17.66 15.68 230.7 827.80 33.13 32.52 17.50 10.53 251.6 860.45 35.75 33.71 16.40 11.00 257.9 875.15 34.46 34.14 16.28 11.31 263.9 909.45 34.60 34.85 16.06 11.96 266.5 905.55 35.38 35.89 15.93 12.58 229.1 756.00 35.85 33.53 16.60 10.66 239.3 769.35 35.68 33.79 16.41 10.85 258.0 793.50 35.35 34.72 16.17 11.41 257.6 801.65 35.04 35.22 15.92 11.91 267.3 819.65 34.07 36.50 16.04 12.85 267.0 808.55 32.20 37.60 16.19 13.58 259.6 774.95 34.32 37.89 16.62 14.21 240.4 711.85 31.08 37.71 17.37 15.56 227.2 694.85 35.73 37.00 18.12 15.83 196.0 638.10 34.11 36.76 18.53 16.41 278.7 774.55 34.79 34.62 15.54 13.10 272.3 757.90 35.77 35.40 15.70 13.63 267.4 753.35 36.44 35.96 16.45 14.51 254.5 704.70 37.82 36.26 17.62 15.38 224.7 666.80 35.07 36.34 18.12 16.10 181.5 568.55 35.26 35.90 19.05 16.73 227.5 653.10 35.56 31.84 16.51 10.58 253.6 704.05 35.73 33.16 16.02 11.28 263.0 709.60 36.46 33.83 15.89 11.91 265.8 726.90 36.26 34.89 15.83 12.65 263.8 697.15 37.20 36.27 16.71 14.06 b. Construct and interpret a plot of the residuals versus the predicted response.
4.3 Consider the simple linear regression model fit to the solar energy data. DATA SETS FOR EXERCISES 555 TABLE B.2 Solar Thermal Energy Test Data y x₁ X₂ X3 X4 xs 271.8 783.35 33.53 40.55 16.66 13.20 264.0 748.45 36.50 36.19 16.46 14.11 238.8 684.45 34.66 37.31 17.66 15.68 230.7 827.80 33.13 32.52 17.50 10.53 251.6 860.45 35.75 33.71 16.40 11.00 257.9 875.15 34.46 34.14 16.28 11.31 263.9 909.45 34.60 34.85 16.06 11.96 266.5 905.55 35.38 35.89 15.93 12.58 229.1 756.00 35.85 33.53 16.60 10.66 239.3 769.35 35.68 33.79 16.41 10.85 258.0 793.50 35.35 34.72 16.17 11.41 257.6 801.65 35.04 35.22 15.92 11.91 267.3 819.65 34.07 36.50 16.04 12.85 267.0 808.55 32.20 37.60 16.19 13.58 259.6 774.95 34.32 37.89 16.62 14.21 240.4 711.85 31.08 37.71 17.37 15.56 227.2 694.85 35.73 37.00 18.12 15.83 196.0 638.10 34.11 36.76 18.53 16.41 278.7 774.55 34.79 34.62 15.54 13.10 272.3 757.90 35.77 35.40 15.70 13.63 267.4 753.35 36.44 35.96 16.45 14.51 254.5 704.70 37.82 36.26 17.62 15.38 224.7 666.80 35.07 36.34 18.12 16.10 181.5 568.55 35.26 35.90 19.05 16.73 227.5 653.10 35.56 31.84 16.51 10.58 253.6 704.05 35.73 33.16 16.02 11.28 263.0 709.60 36.46 33.83 15.89 11.91 265.8 726.90 36.26 34.89 15.83 12.65 263.8 697.15 37.20 36.27 16.71 14.06 b. Construct and interpret a plot of the residuals versus the predicted response.
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:4.3 Consider the simple linear regression model fit to the solar energy data.
DATA SETS FOR EXERCISES 555
TABLE B.2 Solar Thermal Energy Test Data
y
x₁
X₂
X3
X4
Xs
271.8
783.35
33.53
40.55
16.66
13.20
264.0
748.45
36.50
36.19
16.46
14.11
238.8
684.45
34.66
37.31
17.66
15.68
230.7
827.80
33.13
32.52
17.50
10.53
251.6
860.45
35.75
33.71
16.40
11.00
257.9
875.15
34.46
34.14
16.28
11.31
263.9
909.45
34.60
34.85
16.06
11.96
266.5
905.55
35.38
35.89
15.93
12.58
229.1
756.00
35.85
33.53
16.60
10.66
239.3
769.35
35.68
33.79
16.41
10.85
258.0
793.50
35.35
34.72
16.17
11.41
257.6
801.65
35.04
35.22
15.92
11.91
267.3
819.65
34.07
36.50
16.04
12.85
267.0
808.55
32.20
37.60
16.19
13.58
259.6
774.95
34.32
37.89
16.62
14.21
240.4
711.85
31.08
37.71
17.37
15.56
227.2
694.85
35.73
37.00
18.12
15.83
196.0
638.10
34.11
36.76
18.53
16.41
278.7
774.55
34.79
34.62
15.54
13.10
272.3
757.90
35.77
35.40
15.70
13.63
267.4
753.35
36.44
35.96
16.45
14.51
254.5
704.70
37.82
36.26
17.62
15.38
224.7
666.80
35.07
36.34
18.12
16.10
181.5
568.55
35.26
35.90
19.05
16.73
227.5
653.10
35.56
31.84
16.51
10.58
253.6
704.05
35.73
33.16
16.02
11.28
263.0
709.60
36.46
33.83
15.89
11.91
265.8
726.90
36.26
34.89
15.83
12.65
263.8
697.15
37.20
36.27
16.71
14.06
b. Construct and interpret a plot of the residuals versus the predicted response.
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