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    Multiple regression analysis

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    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?

    © BrainMass Inc. brainmass.com October 9, 2019, 10:40 pm ad1c9bdddf
    https://brainmass.com/statistics/regression-analysis/multiple-regression-analysis-228339

    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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