Interpret the constant and its p-value. We model energy use per capita of 131 countries in a.given.year as follows:Lutpes.rS = Bo + B,Lnypcpenn + B2Lnypcpenn2 + B3LnGasprice +BĄLnAnnualprecip + B5TempColdest + B6TempWarmest + B,ffrents + B3LnPop +B,LnLand + D_incomegroups +uThe variables are defined as follows:Lutpes PS = log of total primary energy consumption per capita (ktoe)Lnypepenu =log of GDP per capita (USD)Lnypcpenn2 = square of log of GDP per capita (USD)Ln gasprice = log of pump price for gasoline (USD/liter)LUAnnualprecip log of annual precipitation (mm)Tempacoldest= average temperature for the coldest month in a year (in C)Temp.warmeşt= average temperature for the warmest month in a year (in C)ffrents = Fossil Fuel Rents (% of GDP)LnPop = log of population (in millions)LnLand = log of land area (in km2)LIncomegroup =refers to income groups "1", "2" and "3", low, mid and high incomecountries.**Log" always refers to natural logs or "In" here.Linear regressionNumber of obs131F(11, 119)143.13Prob > F0.0000R-squared0.8941Root MSE.36402RobustIntpes_pcCoef.Std. Err.tP>|t|[95% Conf. Interval]InypcpennInypcpenn2In_gasprice-.95995624732335-2.030.045-1.897006-.0229066.0954567.02561923.730.000.0447282.1461852-.2392021.0566569-4.220.000-.3513885-.1270157temp_coldest-.01857.005238-3.550.001-.0289417-.0081983temp_warmest.0166677.0160091.040.300-.0150318.0483671In_annualprecip.006395.05399540.120.906-.1005213.1133114ffrents.0028204.00285460.990.325-.0028319.0084728Inpop-.0469675.038338-1.230.223-.1228807.0289456Inland.0546541.03289581.660.099-.0104828.119791_Iincomegro_2.1032733.22836480.450.652-.3489118.5554584_Iincomegro_3-.0828519.1007342-0.820.412-.2823156.1166118_cons8.3033362.409653.450.0013.53198913.07468Log referrers to natural logarithm!

Name: Interpret the constant and its p-value. We model energy use per capita
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Description: Interpret the constant and its p-value. We model energy use per capita of 131 countries in a.given.year as follows:Lutpes.rS = Bo + B,Lnypcpenn + B2Lnypcpenn2 + B3LnGasprice +BĄLnAnnualprecip + B5TempColdest + B6TempWarmest + B,ffrents + B3LnPop +B,L

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A First Course in Probability (10th Edition)

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Author:Sheldon Ross

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Interpret the constant and its p-value.

We model energy use per capita of 131 countries in a.given.year as follows:
Lutpes.rS = Bo + B,Lnypcpenn + B2Lnypcpenn2 + B3LnGasprice +
BĄLnAnnualprecip + B5TempColdest + B6TempWarmest + B,ffrents + B3LnPop +
B,LnLand + D_incomegroups +u
The variables are defined as follows:
Lutpes PS = log of total primary energy consumption per capita (ktoe)
Lnypepenu =log of GDP per capita (USD)
Lnypcpenn2 = square of log of GDP per capita (USD)
Ln gasprice = log of pump price for gasoline (USD/liter)
LUAnnualprecip log of annual precipitation (mm)
Tempacoldest= average temperature for the coldest month in a year (in C)
Temp.warmeşt= average temperature for the warmest month in a year (in C)
ffrents = Fossil Fuel Rents (% of GDP)
LnPop = log of population (in millions)
LnLand = log of land area (in km2)
LIncomegroup =refers to income groups "1", "2" and "3", low, mid and high income
countries.
**Log" always refers to natural logs or "In" here.
Linear regression
Number of obs
131
F(11, 119)
143.13
Prob > F
0.0000
R-squared
0.8941
Root MSE
.36402
Robust
Intpes_pc
Coef.
Std. Err.
t
P>|t|
[95% Conf. Interval]
Inypcpenn
Inypcpenn2
In_gasprice
-.9599562
4732335
-2.03
0.045
-1.897006
-.0229066
.0954567
.0256192
3.73
0.000
.0447282
.1461852
-.2392021
.0566569
-4.22
0.000
-.3513885
-.1270157
temp_coldest
-.01857
.005238
-3.55
0.001
-.0289417
-.0081983
temp_warmest
.0166677
.016009
1.04
0.300
-.0150318
.0483671
In_annualprecip
.006395
.0539954
0.12
0.906
-.1005213
.1133114
ffrents
.0028204
.0028546
0.99
0.325
-.0028319
.0084728
Inpop
-.0469675
.038338
-1.23
0.223
-.1228807
.0289456
Inland
.0546541
.0328958
1.66
0.099
-.0104828
.119791
_Iincomegro_2
.1032733
.2283648
0.45
0.652
-.3489118
.5554584
_Iincomegro_3
-.0828519
.1007342
-0.82
0.412
-.2823156
.1166118
_cons
8.303336
2.40965
3.45
0.001
3.531989
13.07468
Log referrers to natural logarithm!

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