The following data show the demand for an airline ticket dependent on the price of this ticket.Price100110120130140150160170180190200210220230Demand 42,308 39,508 32,058 28,558 25,058 22,758 20,538 17,528 15,408 13,248 11,238 8,088 7,428 6,058Price240250260270280290300310320330340350360370Demand5,438 4,918 4,458 4, 028 3,648 3,298 2,988 2,708 2,448 2,368 2,008 1,8081,638 1,488Price380390400410420430440450460470480490500510Demand1,348 1,218 1,108998908818748668608548498458408368Price520530540550560570580590600610620630640650Demand338328318308288268258248228208188168168158For the assumed cubic and log-log regression models, Demand = B9 + B1Price + B2Price? + B3Price + e and In (Demand) = Ba + 81ln(Price) + €, respectively, the followingregression results are available.VariableCubic ModelLog-Log Model85,345.5-587.4415Intercept26.2770N/Ax21.3074N/Ax3-.0010N/AIn(x)N/A-3.2694R20.98100.9820Adjusted R20.97980.9818Standard Error se1,515.45800.2094Assuming that the sample correlation coefficient between Demand and Demand = exp(26.2770 - 3.2694 In(Price) + (0.2094)2/2) is 0.963, what is the predicted demand for a price of$250 found by the model with better fit?

Answered: For the assumed cubic and log-log…

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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