Quantitative Method



Quantitative Method

Detecting Multicollinearity

The process or presence of multicollinearity is a situation that occurs in a regression which presents a strong correlation between explanatory variables. The strong correlation between explained and explanatory variable shows a highly significant model but it becomes completely opposite when it comes to explanatory variables. In practical situations, there should be no correlation between two explanatory variables in a model, i.e. no correlation between the explanatory variables is an ideal situation statistically but it is could be found only in laboratory conditions or in academic examples.

Multicollinearity Statistics

Variables

Tolerance

VIF

AB

0.265

3.776

H

0.254

3.931

3B

0.686

1.457

HR

0.254

3.929

RBI

0.215

4.662

NL OR NOT

0.922

1.084

Variance inflation factor (VIF) - a measure of ...