i) Explain and interpret all Beta-coefficient, with significant value.ii) Explain what Collinearity Statistics suggests. iii) Propose a relevant empirical model to predict Customer Satisfaction.iv) Explain the empirical model proposed in part (iii). Model1 (Constant)ReliabilityEmpathyUnstandardized StandardizedCoefficientsCoefficientsB-.748Std.Error.286.279 .063.090 .096.251 .108.563.090.030 .050CoefficientsaResponsivenessAssuranceTangibilitya. Dependent Variable: SatisfactionBeta.254.073.194.390.028t2.617Correlations.010Zero-Sig. order Partial Part Tolerance VIFCollinearityStatistics4.442.000.000 .592 .300.202.934 .352 .611.066.0422.334.021 .655.163.1066.269.000.684.406 .285.607.545 .042 .043 .028.632 1.582.336 2.980.299 3.346.532 1.879.988 1.013

i) In a regression analysis, the beta-coefficients stand in for the standardised coefficients. They…

Explain and interpret all Beta-coefficient, with significant value. ii) Explain what Collinearity Statistics suggests. iii) Propose a relevant empirical model to predict Customer Satisfaction. iv) Explain the empirical model proposed in part (iii).

Explain and interpret all Beta-coefficient, with significant value. ii) Explain what Collinearity Statistics suggests. iii) Propose a relevant empirical model to predict Customer Satisfaction. iv) Explain the empirical model proposed in part (iii).

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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