The following table gives the regression results of consumption behaviour between female and male. Consumption (C), in RM Model 1 Model 2 Constant 0.7515 0.6587 (0.024) (0.037) Y 0.8603 0.5442 (0.0301) (0.2881) Gen 0.2001 (0.0004) Y*Gen 0.3105 (0.0076) Adjusted R 0.78 0.78 No. of Observations 47 47 Note: Y=income (RM) Gen= Gender ( It is equal to 1 if person is female; 0 is for male) Figures in the parentheses are p- values a) Identify which are the qualitative, quantitative and interaction variable. Refer to Model 1: b) Write the regression equations for female and male. c) Draw the regression lines for female and male on the same diagram. What can you say? d) Interpret all the estimated slope coefficients. e) Conduct an appropriate test to determine whether variable gender is statistically significant at 5%. Should this variable be dropped from this regression model.
The following table gives the regression results of consumption behaviour between female and male. Consumption (C), in RM Model 1 Model 2 Constant 0.7515 0.6587 (0.024) (0.037) Y 0.8603 0.5442 (0.0301) (0.2881) Gen 0.2001 (0.0004) Y*Gen 0.3105 (0.0076) Adjusted R 0.78 0.78 No. of Observations 47 47 Note: Y=income (RM) Gen= Gender ( It is equal to 1 if person is female; 0 is for male) Figures in the parentheses are p- values a) Identify which are the qualitative, quantitative and interaction variable. Refer to Model 1: b) Write the regression equations for female and male. c) Draw the regression lines for female and male on the same diagram. What can you say? d) Interpret all the estimated slope coefficients. e) Conduct an appropriate test to determine whether variable gender is statistically significant at 5%. Should this variable be dropped from this regression model.
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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Question

Transcribed Image Text:The following table gives the regression results of consumption behaviour between
female and male.
Consumption (C), in RM
Model 1
Model 2
Constant
0.7515
0.6587
(0.024)
(0.037)
Y
0.8603
0.5442
(0.0301)
(0.2881)
Gen
0.2001
(0.0004)
Y*Gen
0.3105
(0.0076)
Adjusted R
0.78
0.78
No. of Observations
47
47
Note: Y=income (RM)
Gen= Gender ( It is equal to 1 if person is female; 0 is for male)
Figures in the parentheses are p- values
a) Identify which are the qualitative, quantitative and interaction variable.
Refer to Model 1:
b)
Write the regression equations for female and male.
Draw the regression lines for female and male on the same diagram. What can you
c)
say?
d)
Interpret all the estimated slope coefficients.
e)
Conduct an appropriate test to determine whether variable gender is statistically
significant at 5%. Should this variable be dropped from this regression model.
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