![]() Since the ability to make precise estimates is important to many companies, generally people aim for a VIF within the range of 1-5. The higher the variance, the worse off you may be when it comes to prediction. If the VIF is close to 1 (with 1 typically being the ideal target), then the dependent factor is not heavily impacted by its correlation with other factors. If your VIF number is greater than 10, the included factors are highly correlated to each other and have a great amount of influence. Essentially, the VIF tells you the effect of correlations among your predictors for the returns and costs of a product. It measures how much an dependent factor (such as the sales for a specific product) varies due to the influence of other factors (such as the season/weather). VIF, the Variance Inflation Factor, is used during regression analysis to assess whether certain factors are correlated to each other and the severity of this correlation. ![]()
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