Use the Stata output below to answer the following question. The data used in this analysis is from a sample of airlines. Thevariables used are:fare-avg price of a one-way fare, in dollarsdist- distance of the flight, in miles.reg fare ldist.SourceModelResidual 551.391705TotallfareSSldist_cons875.094374dfThe OLS results suggest that1 323.7026681200243154,594MSCoef. Std. Err.4,595 190444913Number of obsF(1, 4594)Prob > FR-squaredAdj R-squaredRoot MSEt P>|t|.4025646 .0077517 51.93 0.0002.399834 .0521601 46.01 0.0004,5962696.980.00000.36990.3698.34645[95% Conf. Intervall.3873676 .41776172.297575 2.502093a 1% increase in distance is associated with approximately a $.40 increase in the price of the fare.a 1% increase in distance is associated with approximately a .40% increase in the price of the fare.a 1% increase in distance is associated with approximately a 40 % increase in the price of the fare.None of the above.

Answered: Use the Stata output below to answer…

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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The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?
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State the estimated coefficient for time and its interpretation. Also, state what the coefficient of determination is and its interpretation.
(e) Test the hypothesis Ho : B1 = 10 versus H1 :ß, # 10 using a = 0.01. Ho and conclude the slope v 10 at a = 0.01. (d) Test the hypothesis Ho : Bo = 0 versus H1 : Bo + 0 using a = 0.01. Ho and conclude that the intercept be included in the model.

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