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VIF is the abbreviation of variance inflation factor which is a measure of the amount of multicollinearity that exists in a set of multiple regression variables.
*The VIF value being above the upper limit of 10 suggest that there is severe multicollinearity
The VIF Equation:
The VIF value is below the upper limit of 10 (1.353 < 10) therefore it reveals that Wfood is not strongly correlated with the other independent variables and there is no multicollinearity.
Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.
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Primary Model Below is a regression analysis without 17 outliers that have been removed Regression Analysis: wfood versus totexp, income, age, nk The regression equat
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