All Models are Right...Most are Useless


Thaddeus Tarpey

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Conference Proceeding

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Students of statistics are often introduced to George Box's famous quote: "all models are wrong, some are useful." In this talk I argue that this quote, although useful, is wrong. A different and more positive perspective is to acknowledge that a model is simply a means of extracting information of interest from data. The truth is infinitely complex and a model is merely an approximation to the truth. If the approximation is poor or misleading, then the model is useless. In this talk I give examples of correct models that are not true models. I illustrate how the notion of a "wrong" model can lead to wrong conclusions.


This paper was presented at the Joint Statistical Meeting, August 4, 2009, in Washington, DC.

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