By studying a chemical process,expects the yield to be affectedby the levels of two factors, X1and x2.ObservationFactor 1Factor 2Yield(X)(x2)29.1(v,)251.3Number141.9243.429.3251.3343.929.5248.3Observationsrecordedfor444.529.7267.5547.329.9273.0various levels of the two factors47.530.3276.5are shown in the following table.• Interaction between x, and x2 isexpectedknowledge of similar processes.747.930.5270.350.230.7274.9952.830.8285.01053.230.9290.0notbasedon1156.731.5297.01257.031.7302.51363.531.9304.5Units of the factor levels and the1465.332.0309.31571.132.1321.7yieldanalysis.Determine resulting least-squaresequation of Multiple regressionusing matrix approach.ignored for theare1632.532.977.0330.71777.8349.034

Multiple regression using a matrix approach is Y1=β0+β1x1i+β2x2i+...+βpxpi+εi i=1,2,3,...…

Answered: rield to be affected of two factors, x1…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter4: Eigenvalues And Eigenvectors

Section4.6: Applications And The Perron-frobenius Theorem

Problem 25EQ

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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 半 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Coef SE Coef P Constant 321.878 2.483 129.64 0.000 absorb 156.711 6.464 24.24 0.000 S = 3.60498 R-Sq = 98.5% R-Są (adj) - 98.3% SOURCE DF MS F P Regression 1 7639.0 7639.0 587.81 0.000 Residual Error 9 117.0 13.0 Total 10 7756.0 (a) Does the simple linear regression model appear to be…

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rield to be affected of two factors, x1 Observation Number 2 3 recorded for 4 5 s of the two factors the following table. etween X1 and x2 is 7 10