Using Statistical Evidence to Prove Causality (i.e., Causation) to Non-Statisticians

16 Pages Posted: 6 Jul 2007 Last revised: 2 Feb 2017

See all articles by Palmer Morrel-Samuels

Palmer Morrel-Samuels

Employee Motivation and Performance Assessment; University of Michigan at Ann Arbor - School of Public Health

Peter D. Jacobson

University of Michigan School of Public Health

Date Written: July 5, 2007

Abstract

Many writers claim that statistics have become increasingly important in litigation. However, no comprehensive contemporary guide exists for attorneys who want to use statistical data to create effective demonstrative evidence - an issue that is especially important when non-statisticians use statistics to make inferences about causality. In this paper we outline a new theory explaining the perception, comprehension, and recall of quantitative graphs. As an outgrowth of that theory we propose that four cornerstones are essential for inferences of causality in most disciplines: Sufficiency, Necessity, Proximity, and Plausibility. Consistent with this theory, we contend that four hallmarks of causality are critical. These hallmarks show positive evidence of Association, Prediction, and Dose-dependence, as well as negative evidence Ruling Out Alternative Explanations. We close by using recent advances from research in experimental psychology to formulate best-practice examples of how these four hallmarks can be shown in quantitative graphs during litigation.

Keywords: empirical methodology, law and psychology

JEL Classification: C00

Suggested Citation

Morrel-Samuels, Palmer and Morrel-Samuels, Palmer and Jacobson, Peter D., Using Statistical Evidence to Prove Causality (i.e., Causation) to Non-Statisticians (July 5, 2007). Available at SSRN: https://ssrn.com/abstract=995841 or http://dx.doi.org/10.2139/ssrn.995841

Palmer Morrel-Samuels (Contact Author)

Employee Motivation and Performance Assessment ( email )

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Chelsea, MI 48118
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HOME PAGE: http://SurveysForBusiness.com

University of Michigan at Ann Arbor - School of Public Health ( email )

1415 Washington Heights
Ann Arbor, MI 48109-2029
United States
734-368-3348 (Phone)

Peter D. Jacobson

University of Michigan School of Public Health ( email )

109 Observatory
Ann Arbor, MI 48109-2029
United States
734-936-0928 (Phone)
734-764-4338 (Fax)

HOME PAGE: http://www.sph.umich.edu/~pdj/

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