PreprintArticleVersion 2Preserved in Portico This version is not peer-reviewed
A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics
Version 1
: Received: 13 September 2017 / Approved: 14 September 2017 / Online: 14 September 2017 (09:19:58 CEST)
Version 2
: Received: 15 December 2017 / Approved: 17 December 2017 / Online: 17 December 2017 (08:48:29 CET)
How to cite:
Lang, M. A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics. Preprints2017, 2017090054. https://doi.org/10.20944/preprints201709.0054.v2
Lang, M. A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics. Preprints 2017, 2017090054. https://doi.org/10.20944/preprints201709.0054.v2
Lang, M. A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics. Preprints2017, 2017090054. https://doi.org/10.20944/preprints201709.0054.v2
APA Style
Lang, M. (2017). A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics. Preprints. https://doi.org/10.20944/preprints201709.0054.v2
Chicago/Turabian Style
Lang, M. 2017 "A Quick Guide to Statistical Modeling Design Defects, Product Liability and the Protective Properties of Suboptimal Nonparametric and Robust Statistics" Preprints. https://doi.org/10.20944/preprints201709.0054.v2
Abstract
Statistical modeling lies at the heart of product design and development throughout numerous engineering disciplines, especially since processing large amounts of data has become increasingly ubiquitous. While mathematical statistics provide elegant guidance pertaining to the question of whether or not some particular underlying modeling assumptions are justified and appropriate, when pursuing a more comprehensive assessment of product design and development other considerations often increase in significance. Therefore, we will examine and analyze the tedious interactions and implications of statistical modeling choices and product liability exposure. To the best of our knowledge, this paper is the first to draw attention to and explore some often overlooked or oversimplified dangers and pitfalls that enter the equation when product design heavily relies on statistical modeling. In particular, through a diligent analysis of both statistical and legal aspects we will explore how statistically optimal procedures may yield far from optimal outcomes in terms of product liability when applied to actual real life problems and why suboptimal nonparametric or robust approaches may constitute better alternatives.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.