1. Model 1: OLS, using observations 1-706 Dependent variable: RST Coefficient Std. Error t-ratio p-value const 3586.38 38.9124 92.17 <0.0001 * TOTWRK −0.150746 0.0167403 −9.005 <0.0001 * Mean dependent var 3266.356 S.D. dependent var 444.4134 Sum squared resid 1.25e+08 S.E. of regression 421.1357 R-squared 0.103287 Adjusted R-squared 0.102014 F(1, 704) 81.08987 P-value(F) 1.99e-1810538.19 Log-likelihood −5267.096 Akaike criterion 10538.19 Schwarz criterion 10547.31 Hannan-Quinn 10541.71 RSTi =3586.38−0.150746 x TOTWRKi , R2=0.103287,SER=421.1357 (38.9124) (0.0167403) Question? A- The researcher claims that the model lacks a fundamental principle, namely, the impact of the worker’s gender on their efficiency. The researcher further claims that Men on average take more resting time than women. To clarify the researcher’s claim, add the binary variable MALE into your model, and write down the estimated results for the following population regression function. RST? = ?0 + ?1TOTWRK? + ?2MALE? + u? B- Furthermore, how do you interpret the estimated slope coefficient of the binary variable MALE? Is the researcher’s claim that men on average take more resting time than women consistent with your estimated results? Why or why not?

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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Question

Model 1: OLS, using observations 1-706

Dependent variable: RST

	Coefficient	Std. Error	t-ratio	p-value
const	3586.38	38.9124	92.17	<0.0001	***
TOTWRK	−0.150746	0.0167403	−9.005	<0.0001	***

Mean dependent var	3266.356	S.D. dependent var	444.4134
Sum squared resid	1.25e+08	S.E. of regression	421.1357
R-squared	0.103287	Adjusted R-squared	0.102014
F(1, 704)	81.08987	P-value(F)	1.99e-1810538.19
Log-likelihood	−5267.096	Akaike criterion	10538.19
Schwarz criterion	10547.31	Hannan-Quinn	10541.71

RST_i=3586.38−0.150746 x TOTWRK_i, R²=0.103287,SER=421.1357

(38.9124) (0.0167403)

Question?

A- The researcher claims that the model lacks a fundamental principle, namely, the impact of the worker’s gender on their efficiency. The researcher further claims that Men on average take more resting time than women. To clarify the researcher’s claim, add the binary variable MALE into your model, and write down the estimated results for the following population regression function.

RST_? = ?₀+ ?₁TOTWRK_?+ ?₂MALE_? + u_?

B- Furthermore, how do you interpret the estimated slope coefficient of the binary variable MALE? Is the researcher’s claim that men on average take more resting time than women consistent with your estimated results? Why or why not?

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