Collinearity versus Correlation




What is the difference between “high collinearity between independent variables” and “high correlation between independent variables” . Which one do i want and which one should i not use while creating a model?


Correlation measures the relationship between two variables. When these two variables are so highly correlated that they explain each other (to the point that you can predict the one variable with the other), then we have Collinearity.


Correlation is the measure of dependency on each other while collinearity is the rate of change in one variable respect to other in linear fashion.


Correlation refers to an increase/decrease in a dependent variable with an increase/decrease in an independent variable. Collinearity refers to two or more independent variables acting in concert to explain the variation in a dependent variable.


Thank you @pjoshi15, @shaashaank, @jprakash0205 for the clarification.