Generate and explain the derivation of insights using regression analysis and its associated visualization Differentiate between the signals identified by business analytics and the noise that is inherent in the system. SUMMARY OUTPUTRegression StatisticsMultiple R0.248625R Square0.061815Adjusted R Squa-0.032Standard Error3.812356Observations12ANOVAdfSignificance FSSMSFRegression9.576115842 9.576116 0.6588743330.435852855Residual10145.3405508 14.53406Total11154.9166667Coefficients Standard Errort StatP-valueLower 95%Upper 95%Lower 95.0% Upper 95.0%Intercept6.9610444.596238954 1.514509 0.160845195-3.28001492 17.20210225-3.2800149217.20210225Flight Time2.7269433.359501282 0.811711 0.435852855-4.758492044 10.21237862 -4.75849204410.21237862 AirplanesFoldsFlight TimeFlight Time171.22.5111.633131.162.450.75591.181.5y = -0.0013x + 1.3365• R2 = 0.0002102.017121.48Flight Time1881.73.... Linear (Flight Time )9141.230.510151.311160.9612171.326.8.101214Axis TitleCUAAA A0DY OUTDUTAirplanes/ Folds

Given: Regression analysis output

Generate and explain the derivation of insights using regression analysis and its associated visualization Differentiate between the signals identified by business analytics and the noise that is inherent in the system.

Generate and explain the derivation of insights using regression analysis and its associated visualization Differentiate between the signals identified by business analytics and the noise that is inherent in the system.

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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