EconHM19 - Question #1 Multicollinearity can best be...

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Question #1 Multicollinearity can best be described as the condition in which the: independent variables in a regression have a high degree of correlation with one another Multicollinearity is likely to be causing problems with your regression results if: Hint: there are 2 correct answers . you have a high R?but the Overall Model F-test indicates that the model is not valid the independent variables have one or more correlation coefficients above . 50 the independent variables have one or more correlation coefficients near 0 you have a very low R?but the Overall Model F-test indicates a valid model the Overall Model F-test indicates a valid model but the individual t- tests indicate none of the independent variables are linearly related to the dependent variable the independent variables have one or more correlation coefficients above .80 a majority of independent variables appear not to be linearly related to the dependent variable Multicollinearity can result in: Hint: there are 4 correct answers . an inability to interpret R? an increased value for SST a decrease in the absolute value of the Overall Model F-test test statistic a decrease in the absolute value of the individual t-test test statistics an increased p-value for the individual t-tests an inflated value for the standard error of the regression
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This note was uploaded on 02/11/2010 for the course ECON 203 taught by Professor Petry during the Spring '09 term at University of Illinois, Urbana Champaign.

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EconHM19 - Question #1 Multicollinearity can best be...

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