It has been shown that the minimum sum of absolute errors regression is more robust than the least squares regression for some types of outliers. Further it has been shown that even if the value of certain variable for an observation is changed with in limits, it leaves the fitted minimum sum of absolute errors regression unchanged. I will discuss this special property of the minimum sum of absolute errors regression for the simple and the multiple linear regression and illustrate the results with examples.