An article presents the results of an experiment in which the surface roughness (in μm) was measured for 15 D2 steel specimens and compared with the roughness predicted by a neural network model. The results are presented in the following table. TRUE Value (x) Predicted Value (y) 0.45 0.400 0.82 0.7 0.54 0.52 0.41 $0.39 0.77 0.74 0.79 0.78 0.25 0.27 0.62 0.6 0.91 0.87 0.52 0.51 1.02 0.91 0.6 0.71 0.58 0.5 0.87 0.91 1.06 1.04

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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Computer a 95 % confidence interval for the mean prediction when the true roughness is 0.8 um
An article presents the results of an experiment in which the surface roughness (in μm) was measured for 15 D2 steel
specimens and compared with the roughness predicted by a neural network model. The results are presented in the
following table.
TRUE Value (x)
Predicted Value (y)
Check my work
0.45
0.400
0.82
0.7
0.54
0.52
0.41
0.39
0.77
0.74
0.79
0.78
0.25
0.27
0.62
0.6
0.91
0.87
0.52
0.51
1.02
0.91
0.6
0.71
0.58
0.5
0.87
0.91
1.06
1.04
To check the accuracy of the prediction method, the linear model y= Bo+B1x+ & is fit. If the prediction method is
accurate, the value of ẞo will be 0 and the value of ẞ1 will be 1.
Note: This problem has a reduced data set for ease of performing the calculations required. This differs from the data
set given for this problem in the text.
Transcribed Image Text:An article presents the results of an experiment in which the surface roughness (in μm) was measured for 15 D2 steel specimens and compared with the roughness predicted by a neural network model. The results are presented in the following table. TRUE Value (x) Predicted Value (y) Check my work 0.45 0.400 0.82 0.7 0.54 0.52 0.41 0.39 0.77 0.74 0.79 0.78 0.25 0.27 0.62 0.6 0.91 0.87 0.52 0.51 1.02 0.91 0.6 0.71 0.58 0.5 0.87 0.91 1.06 1.04 To check the accuracy of the prediction method, the linear model y= Bo+B1x+ & is fit. If the prediction method is accurate, the value of ẞo will be 0 and the value of ẞ1 will be 1. Note: This problem has a reduced data set for ease of performing the calculations required. This differs from the data set given for this problem in the text.
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