JSM Preliminary Online Program
This is the preliminary program for the 2009 Joint Statistical Meetings in Washington, DC.

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Activity Number: 290
Type: Invited
Date/Time: Tuesday, August 4, 2009 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistical Education
Abstract - #302873
Title: All Models are Right . . . Most Are Useless
Author(s): Thaddeus Tarpey*+
Companies: Wright State University
Address: Department of Mathematics and Statistics, Dayton, OH, 45435,
Keywords: regression analysis ; model underpecification ; finite mixture models ; maximum likelihood estimation
Abstract:

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.

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