Explain why two perfectly multicollinear regressors cannot be included in a linear multiple regression. If those...
Explain why two perfectly multicollinear regressors cannot be included in a linear multiple regression. If those same two regressors were not perfectly collinear but highly collinear what difference, or differences, would that make?
Homework Answers
Two perfectly multicollinear regressors cannot be included in a linear multiple regression because it undermines the statistical significance of the independent variables in the regression equation, thereby giving insignificant results of the regression equation, as the regressors would be affecting each other.
If instead of being perfectly multicollinear, the regressors were not perfectly collinear, they would still be affecting each other, leading to a wider confidence interval and thus lower statistical significance of the regressors.
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Explain why two perfectly multicollinear regressors cannot be
included in a linear multiple regression. If those...
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A multiple regression includes two regressors: Use the tool palette to the right to answer the following questions. What is the expected change in Yif X, increases by 10 units and X2 is unchanged? The expected change in Yif X, increases by 10 units and X2 is unchanged is(Properly format your expression using the tools in the palette. Hover over tools to see keyboard shortcuts. E.g, a subscript can be created with the_character)
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Explain why we cannot estimate a linear-log or log-log version
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finpro f i-β0+ β 1 treatment i + β 2 perc female+ β, perc momsec+ β 4 perc dadsectu
finpro f i-β0+ β 1 treatment i + β 2 perc female+ β, perc momsec+ β 4 perc dadsectu
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