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    Multiple regression analysis

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    Answer one of your choice: A, B, C, or D

    A. (a) List two limitations of bivariate regression (in respect to multiple regression.) (b) Why is estimating a multiple regression model just as easy as bivariate regression?

    B. (a) What is the role of the F test in multiple regression? (b) How is the F statistic determined from the ANOVA table? (c) Why are F-tables rarely needed for the F test?

    C. (a) What does a coefficient of determination (R²) measure? (b) When R² and R² adj differ considerably, what does it indicate?

    D. (a) What is a binary predictor? (b) How do we test a binary predictor for significance?

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    The model adequacy of a multiple regression model is measure using the coefficient of determination R2. It is the proportion of variability in a data set that is accounted for by the statistical model. It provides a measure of how well future outcomes are likely to be predicted by the model. The general definition of R2 is where SSR is the sum of squares due to regression, SST is the total sum of squares. 0≤R2≤1.
    R2 is a statistic that will give some information about the goodness of fit of a ...

    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.