Dependent Variable: CO2 Method: Least Squares Date: 04/20/17 Time: 09:46 Sample: 1990 2013 Included observations: 24 Variable Coefficient Std. Error t-Statistic Prob. C 2.002813 6.458672 0.310097 0.7597 GDP 0.022114 0.011872 1.862670 0.0773 ENERGY -0.734352 0.328388 -2.236233 0.0369 POP 0.203927 0.293686 0.694371 0.4954 R-squared 0.825079 Mean dependent var 3.625982 Adjusted R-squared 0.798841 S.D. dependent var 0.108170 S.E. of regression 0.048515 Akaike info criterion -3.062883 Sum squared resid 0.047074 Schwarz criterion -2.866541 Log likelihood 40.75460 Hannan-Quinn criter. -3.010793 F-statistic 31.44583 Durbin-Watson stat 1.410912 Prob(F-statistic) 0.000000 a-Write down the economic function for the above estimation by using the information obtained from above table. b- Write down the economic model for the above estimation by using the information obtained from above table.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
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Dependent Variable: CO2 |
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Method: Least Squares |
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Date: 04/20/17 Time: 09:46 |
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Sample: 1990 2013 |
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Included observations: 24 |
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Variable |
Coefficient |
Std. Error |
t-Statistic |
Prob. |
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C |
2.002813 |
6.458672 |
0.310097 |
0.7597 |
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GDP |
0.022114 |
0.011872 |
1.862670 |
0.0773 |
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ENERGY |
-0.734352 |
0.328388 |
-2.236233 |
0.0369 |
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POP |
0.203927 |
0.293686 |
0.694371 |
0.4954 |
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R-squared |
0.825079 |
Mean dependent var |
3.625982 |
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Adjusted R-squared |
0.798841 |
S.D. dependent var |
0.108170 |
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S.E. of regression |
0.048515 |
Akaike info criterion |
-3.062883 |
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Sum squared resid |
0.047074 |
Schwarz criterion |
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-2.866541 |
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Log likelihood |
40.75460 |
Hannan-Quinn criter. |
-3.010793 |
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F-statistic |
31.44583 |
Durbin-Watson stat |
1.410912 |
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Prob(F-statistic) |
0.000000 |
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- a-Write down the economic
function for the above estimation by using the information obtained from above table.
- b- Write down the economic model for the above estimation by using the information obtained from above table.
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