Shown here are the data for y and three predictors, x,, x2,and x3. A multiple regression analysis has been done onthese data; the Minitab results are given. Comment onthe outcome of the analysis in light of the data.yX2X394211204972519893221184952720090291182912011599118114794251969826228992424290281162922311809625219Regression Analysis: Y versus X1, X2, X3The regression equation isY = 87.9 - 0.256 X, - 2.71 X2 + 0.0706 X3PredictorCoefSE CoefTPConstant87.8903.44525.510.000X1-0.256120.08317-3.080.013X2-2.71370.7306-3.710.005X30.070610.013535.220.001S = 0.850311R-Sq = 94.1%R-Sq (adj) = 92.1%Analysis of VarianceSourceDFMSRegression103.18534.39547.570.000Residual Error6.5070.723Total12109.692

Given Y=87.9-0.256X1 -2.71X2+0.0706X3 S=0.850311 R square = 94.18

Shown here are the data for yand three predictors, X1, X2, and x3. A multiple regression analysis has been done on these data; the Minitab results are given. Comment on the outcome of the analysis in light of the data.

Shown here are the data for yand three predictors, X1, X2, and x3. A multiple regression analysis has been done on these data; the Minitab results are given. Comment on the outcome of the analysis in light of the data.

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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