Statistical String Theory for Courts: If the Data Don't Fit...
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. This tool is path-breaking and will have an extensive impact on how a wide variety of cases are decided. 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 expert witnesses often make mistaken assumptions about what probability distributions are appropriate for their analyses. Using the wrong probability distribution can lead to invalid fac¬tual 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 variety of data can alleviate judicial fact finders of the difficult task of trying to correctly select among competing distributions offered by battling experts. 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. We strongly encourage judges, policymakers, and legal practitioners to become acquainted with this technique, so they can both make use of and understand legal arguments based on it, and produce better policy, better law, and better justice for individuals w find themselves caught in a “statistical maze” and at the mercy of the courts.
David F. Babbel. 2008. "Statistical String Theory for Courts: If the Data Don't Fit..." ExpressO
Available at: http://works.bepress.com/davidfbabbel/1