I am trying to understand the basic difference between both . As per what i have read through various links, previously asked questions and videos -
Correlation means - two variables vary together, if one changes so does the other but it does not imply collinearity or that one can explain the other.
VIF - Inflation in the variance of the regression coefficients ?( due to the col-linearity existing among predictors )
I am still confused around -
Variance inflation we mean is how inflated the regression coefficients are due to two or more collinear predictors ?
High VIF( > 10) implies high correlation but vice versa is not true ? Can this be explained with an example through variables ?