TABLE B.2 Solar Thermal Energy Test Data y X₂ 271.8 783.35 33.53 264.0 748.45 36.50 238.8 684.45 34.66 230.7 827.80 33.13 251.6 860.45 35.75 257.9 875.15 34.46 263.9 909.45 34.60 266.5 905.55 35.38 229.1 756.00 35.85 239.3 769.35 35.68 258.0 793.50 35.35 257.6 801.65 35.04 X3 40.55 36.19 37.31 32.52 33.71 34.14 34.85 35.89 33.53 33.79 34.72 35.22 X₂ 16.66 16.46 17.66 17.50 16.40 16.28 16.06 15.93 16.60 16.41 16.17 15.92
TABLE B.2 Solar Thermal Energy Test Data y X₂ 271.8 783.35 33.53 264.0 748.45 36.50 238.8 684.45 34.66 230.7 827.80 33.13 251.6 860.45 35.75 257.9 875.15 34.46 263.9 909.45 34.60 266.5 905.55 35.38 229.1 756.00 35.85 239.3 769.35 35.68 258.0 793.50 35.35 257.6 801.65 35.04 X3 40.55 36.19 37.31 32.52 33.71 34.14 34.85 35.89 33.53 33.79 34.72 35.22 X₂ 16.66 16.46 17.66 17.50 16.40 16.28 16.06 15.93 16.60 16.41 16.17 15.92
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
a. Construct a normal probability plot of the residuals. Does there seem to be any problem
with the normality assumption?
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