The regression model Y=X!+" allows for Y being measured with error by having the " term, but what if the X is measured with error? In other words, what if the X we see is not the X used to generate Y? It is not unreasonable that there might be errors in measuring X. For example, consider the problem of determining the effects of being exposed to a potentially hazardous substance such as secondhand tobacco smoke. Such exposure would be a predictor in such a study, but clearly it is very hard to measure this exactly over a period of years.