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1 : Multicollinearity in simple regression X

1 : Multicollinearity in simple regression X

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Figure 1.1 : Multicollinearity in simple regression X
Figure 1.2 : Multicollinearity in multiple regression
Figure 2.1 : Picket Fences illustrations
Figure 2.2 : The choice of VIF value against the R-square value.
+21 Figure 3.3 : The sampling distribution of biased and unbiased estimator
Comparing three methods of handling multicollinearity using simulation approach
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In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory variables. A frequent obstacle is that several of the explanatory variables will vary in rather similar ways. This phenomenon called multicollinearity, is a common problem i...
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... Adnan [18] proposed that the primary goal of regression analysis is to explain the variability in response variables by linking it to proportional variations in explanatory variables. However, this becomes challenging when explanatory variables vary in similar ways, resulting in multicollinearity-a common problem in regression analysis. ...
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