Refer to the following computer output from estimating the parameters of the nonlinear modelY=aRbsc7dThe computer output from the regression analysis is:DEPENDENT VARIABLE: LNY R-SQUARE32 0.7766OBSERVATIONS:VARIABLEINTERCEPTLNRP-VALUE ON F0.0001PARAMETER ESTIMATE STANDARD ERROR T-RATIO-0.6931F-RATIO4.66-0.448.2832.440.321.36-2.173.43-1.83P-VALUE1.800.0390LNS0.24LNT4.60Based on the information in the table, the nonlinear relation can be transformed into the following linear regression model:Multiple Choicein Y= 1n a.ln R.1n S.1n Tin Y= 1na + b1nR+ cins + din T1n Y = 1n(aRb SC7d)Y = 1n(aRb Sc7d)0.00190.07740.0826

Given information: We have given a non-linear model i.e., Y = aRbScTd In order to transform the…

Refer to the following computer output from estimating the parameters of the nonlinear model Y=aRbSCTd The computer output from the regression analysis is: DEPENDENT VARIABLE: LNY R-SQUARE OBSERVATIONS: 32 0.7766 VARIABLE INTERCEPT F-RATIO 32.44 P-VALUE ON F 0.0001 PARAMETER ESTIMATE STANDARD ERROR T-RATIO -2.17 3.43 -0.6931 4.66 -0.44 8.28 P-VALUE 0.0390 0.0019 0.0774 0.0826 0.32 LNR 1.36 LNS 0.24 -1.83 LNT 4.60 1.80 Based on the information in the table, the nonlinear relation can be transformed into the following linear regression model:

Refer to the following computer output from estimating the parameters of the nonlinear model Y=aRbSCTd The computer output from the regression analysis is: DEPENDENT VARIABLE: LNY R-SQUARE OBSERVATIONS: 32 0.7766 VARIABLE INTERCEPT F-RATIO 32.44 P-VALUE ON F 0.0001 PARAMETER ESTIMATE STANDARD ERROR T-RATIO -2.17 3.43 -0.6931 4.66 -0.44 8.28 P-VALUE 0.0390 0.0019 0.0774 0.0826 0.32 LNR 1.36 LNS 0.24 -1.83 LNT 4.60 1.80 Based on the information in the table, the nonlinear relation can be transformed into the following linear regression model:

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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