Statistical String Theory for Courts: If the Data Don't Fit . . . .

Wharton Financial Institutions Center Working Paper No. 08-27

33 Pages Posted: 31 Jul 2008

See all articles by David F. Babbel

David F. Babbel

University of Pennsylvania - The Wharton School - Finance and Insurance Departments; CRA International

Vincent James Strickler

Utah State University - Department of Political Science

Ricki Dolan

University of Texas at Austin

Date Written: July 15, 2008

Abstract

The primary purpose of this article is to provide courts with an important new tool for applying the correct probability distribution to a given legal question. In areas as diverse as criminal prosecutions and civil lawsuits alleging securities fraud, courts must assess the relevance and reliability of statistical data and the inferences drawn therefrom. But, courts and ex-pert witnesses often make mistaken assumptions about what probability distributions are appropriate for their analyses. Using the wrong probability distribution can lead to invalid factual conclusions and unjustified legal outcomes. To deal with this problem, we propose the use of a unifying "statistical string theory" - the g-and-h distribution - in legal settings. This parent distribution subsumes many other distributions and spans the widest range of possible skewness-kurtosis combinations. The capacity of the g-and-h distribution to accommodate such a wide variety of data can alleviate judicial fact finders of the difficult task of trying to correctly select among competing distributions. Finally, we report the successful use of this statistical tool in a trial setting for financial data analysis - showing that it can produce more accurate inferences, than those drawn from alternative distributions, and these differences can be judicially decisive.

Suggested Citation

Babbel, David F. and Strickler, Vincent James and Dolan, Ricki, Statistical String Theory for Courts: If the Data Don't Fit . . . . (July 15, 2008). Wharton Financial Institutions Center Working Paper No. 08-27, Available at SSRN: https://ssrn.com/abstract=1188871 or http://dx.doi.org/10.2139/ssrn.1188871

David F. Babbel (Contact Author)

University of Pennsylvania - The Wharton School - Finance and Insurance Departments ( email )

215 Wakefield Road
Bryn Mawr, PA 19010
United States
610-527-1839 (Phone)

CRA International ( email )

John Hancock Tower
200 Clarendon Street, T-33
Boston, MA 02116-5092
United States
610-527-1839 (Phone)

Vincent James Strickler

Utah State University - Department of Political Science ( email )

0725 University Blvd.
Logan, UT 84322-0725
United States
(435) 797-8017 (Phone)

Ricki Dolan

University of Texas at Austin ( email )

2317 Speedway
Austin, TX 78712
United States

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