The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a function of the cost x of modifying the fleet. A first proposal is the quadratic modelE(y) = β0 + β1x + β2x2Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers? a) Fit the model to the data, then construct a residual plot versus x. Do you detect anytrends? Any outliers?E(y) = Bo + Bix + B2x?E(y) = (-18.62) + (0.31)x + B2x?x|125160801621109014085150501152y|xy 2250x2 | 15625 25600 6400 26244 12100 8100 19600 7225 22500 2500 = 145,89418323763301025217251207205994660 270 42008503750 100 = 23,914B1= nxy - xxnx - (Ex)?B1= 10 (23,914) – (1152)( 172)10 (145,894) – (1152)2Bo= 172 - (0.31...)(1152)B1= 239140 – 198144101458940 – 1327104Bo= 172 – 358.2283443065627B1= 4099610131836Bo = (-18.62283443065627)B1= 0.3109621044327801Bo= (-18.62)B1= 0.31Normal P-P Plot of Regression Standardized ResidualDependent Variable: IMPROVE10

The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a function of the cost x of modifying the fleet. A first proposal is the quadratic model E(y) = β0 + β1x + β2x2 Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers?

The naval base would like to model the projected percentage increase y in fleet effectiveness by the end of the decade as a function of the cost x of modifying the fleet. A first proposal is the quadratic model E(y) = β0 + β1x + β2x2 Fit the model to the data, then construct a residual plot versus x. Do you detect any trends? Any outliers?

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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