Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the regression coefficients impossible. Including the sum of explanatory variables in the regression analysis would, for instance, lead to this problem. Estimated multi co linearity can also cause problems while estimating regression coefficients. In particular if multiple correlations for the regression of the particular explanatory variable on the others is high, then the variance of corresponding estimated regression coefficient will also be quite high.