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Multiple regression analysis

Researcher created a regression models to predict BirthRate (births per 1,000) using the following five predictors (Independent Variables):
+ Life Exp (life expectancy in years)
+ Inf Mort (infant mortality rate)
+ Density (population density per square kilometer)
+ GDP Cap (Gross Domestic Product per capita)
+ Literate (literacy percent)

SUMMARY OUTPUT

Regression Statistics
Multiple R 0.910
R Square 0.812
Adjusted R Square 0.806
Standard Error 5.287
Observations 153

ANOVA
df SS MS F Significance F
Regression 5 17734.58 3546.92 126.88 0.000
Residual 147 4109.26 27.95
Total 152 21843.84

Regression output
Coefficients Standard Error t Stat P-value
Intercept 38.9839 6.3242 6.1643 0.0000
LifeExp -0.0405 0.0757 -0.5346 0.5937
InfMort 0.1266 0.0273 4.6386 0.0000
Density -0.0003 0.0006 -0.4843 0.6289
GDPCap -0.0001 0.0001 -2.0319 0.0440
Literate -0.2191 0.0289 -7.5774 0.0000

A. What is the Dependent Variable?

B. Interpret these results. Address the following
1. Coefficient of correlation, r (Multiple R)

2. R Square. How much variation is explained?

Solution Summary

The solution provides step by step method for the calculation of multiple regression model . Formula for the calculation and Interpretations of the results are also included.

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