Based on the regression results, answer the following questions* A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEOs, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for the year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the null and alternative hypothesis that Excel is testing in reporting the tstats above? g) What is the effect on income of a person being a CEO versus not a CEO?
Based on the regression results, answer the following questions* A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEOs, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for the year 1999, and ASSETS is the natural logarithm of the total assets of the company. Based on the regression results, answer the following questions e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? f) What is the null and alternative hypothesis that Excel is testing in reporting the tstats above? g) What is the effect on income of a person being a CEO versus not a CEO?
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
*Based on the regression results, answer the following questions*
A sample of data is collected (from 1999 and 2000) concerning the compensation of the executives (compensation is measured in 1000’s of $’s) of a number of public companies along with other firm-specific data. The dependent variable is total compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and =0 for individuals who are not CEOs, EMPL is total employees, MKTVAL is the natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR is a dummy variable = 1 for the year 2000 and =0 for the year 1999, and ASSETS is the natural logarithm of the total assets of the company.
Based on the regression results, answer the following questions
e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know?
f) What is the null and alternative hypothesis that Excel is testing in reporting the tstats above?
g) What is the effect on income of a person being a CEO versus not a CEO?
Transcribed Image Text:1) A sample of data is collected (from 1999 and 2000) concerning the compensation of
the executives (compensation is measured in 1000's of $'s) of a number of public
companies along with other firm-specific data. The dependent variable is total
compensation, CEOANN is a dummy variable =1 for an individual who is a CEO and
=0 for individuals who are not CEO's, EMPL is total employees, MKTVAL is the
natural logarithm of the market value of the firm, EPSIN is earnings per share, YEAR
is a dummy variable = 1 for the year 2000 and =0 for year 1999, and ASSETS is the
natural logarithm of the total assets of the company.
a) Complete the table below
Regression
Statistics
Multiple R
R Square
Adjusted R Square
Standard Error
Observations
490
1000
ANOVA
df
SS
MS
Significance F
4.3E-56
Regression
Residual
4975177517 829196252
52.2
15739811503 15850767
Total
Lower 95% Upper 95%
-4382.4
t Stat
P-value
Coefficients Standard Error
634.8
3.45E-18
1.15E-11
3.11E-05
1.18E-16
-5628.1
-8.87
-6873.8
Intercept
CEOANN
EMPL
МKTVAL
EPSIN
2254.2
328.2
1610.0
2898.3
16.3
3.9
4.18
680.8
1093.8
8.43
-3.54
887.3
105.2
49.6
0.00042
-272.7
-78.2
-175.5
0.14
-123.1
876.7
376.8
254.7
YEAR DUM
ASSETS
0.84
0.40
-124.1
311.2
93.5
110.9
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