Rajarshi Guha wrote: > Hi, > I have question regarding the interpretation of the standard error of > prediction in linear regression. As I understand this value is the > variance of the error term for the predicted value in question. > > Is it possible to interpret this value as some sort of a reliability of > the prediction?
Reliability is not a word statistician would use in this particular instance. We would probably say it is a measure of the precision of the prediction. > That is, a low value of SEP would indicate that the > predicted value is more reliable (even though the residual might be high) > compared to the situation with a high value of SEP? A low SEP is more precise. A high SEP is less precise. > If the above is not possible could anybody explain in what way the > residual of a prediction is related to the standard error of the > prediction? Residual estimates the error at a single data point. SEP estimates the precision of the fitted line. These two are not the same. Any particular measurement is made up of a true value plus some noise. Noise may be high for one measurement and low for another and almost zero for a third. However, when you fit a line, you are smoothing out all of the noise, to try to uncover structure. How well you uncover the structure is reflected in the SEP of a prediction. -- Paige Miller Eastman Kodak Company paige dot miller at kodak dot com http://www.kodak.com "It's nothing until I call it!" -- Bill Klem, NL Umpire "When you get the choice to sit it out or dance, I hope you dance" -- Lee Ann Womack . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
