Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 334 342 355 363 365 372 381 Here is regression output from Minitab: Predictor Constant absorb S 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total R-Sq 98.5% DF SE Coef 2.483 6.464 1 9 10 SS 7639.0 117.0 7756.0 T 129.64 24.24 0.491 0.554 0.651 400 412 420 MS 7639.0 13.0 0.000 0.000. R-Sq (adj) 98.3% P F 587.81 (a) Does the simple linear regression model appear to be appropriate? Explain. Yes, a scatter plot of the data shows a strong, linear pattern, and 2 = 98.5%. Yes, a scatter plot of the data shows a weak, linear pattern, and r2 = 98.5%. No, a scatter plot of the data shows a strong, linear pattern, and r2 = 98.5%. O No, a scatter plot of the data shows a weak, non-linear pattern, and r2 = 98.5%. P 0.000 (b) What wrinkle resistance angle would you predict for a fabric specimen having an absorbance of 0.285? (Round your answer to two decimal places.) ▸ (c) What would be the estimate of the expected wrinkle resistance angle when absorbance is 0.285? (Round your answer to two decimal places.)
Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 334 342 355 363 365 372 381 Here is regression output from Minitab: Predictor Constant absorb S 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total R-Sq 98.5% DF SE Coef 2.483 6.464 1 9 10 SS 7639.0 117.0 7756.0 T 129.64 24.24 0.491 0.554 0.651 400 412 420 MS 7639.0 13.0 0.000 0.000. R-Sq (adj) 98.3% P F 587.81 (a) Does the simple linear regression model appear to be appropriate? Explain. Yes, a scatter plot of the data shows a strong, linear pattern, and 2 = 98.5%. Yes, a scatter plot of the data shows a weak, linear pattern, and r2 = 98.5%. No, a scatter plot of the data shows a strong, linear pattern, and r2 = 98.5%. O No, a scatter plot of the data shows a weak, non-linear pattern, and r2 = 98.5%. P 0.000 (b) What wrinkle resistance angle would you predict for a fabric specimen having an absorbance of 0.285? (Round your answer to two decimal places.) ▸ (c) What would be the estimate of the expected wrinkle resistance angle when absorbance is 0.285? (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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Transcribed Image Text:Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as
determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and
y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t
x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651
y
334 342 355
363
365 372 381
400
392
412 420
Here is regression output from Minitab:
Predictor
Constant
absorb
S = 3.60498
Coef
321.878
156.711
SOURCE
Regression
Residual Error
Total
R-Sq= 98.5%
DF
SE Coef
2.483
6.464
1
9
10
SS
7639.0
117.0
7756..0
T
129.64
24.24
P
0.000
0.000.
R-Sq (adj) 98.3%
MS
7639.0
13.0
F
587.81
(a) Does the simple linear regression model appear to be appropriate? Explain.
O Yes, a scatter plot of the data shows a strong, linear pattern, and r2 = 98.5%.
Yes, a scatter plot of the data shows a weak, linear pattern, and r² = 98.5%.
No, a scatter plot of the data shows a strong, linear pattern, and 2 = 98.5%.
No, a scatter plot of the data shows a weak, non-linear pattern, and r2 = 98.5%.
P
0.000
(b) What wrinkle resistance angle would you predict for a fabric specimen having an absorbance of 0.285? (Round your answer to two decimal places.)
►
(c) What would be the estimate of the expected wrinkle resistance angle when absorbance is 0.285? (Round your answer to two decimal places.)
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