Why Study Statistics?

How Statistics Improves the World

Why study statistics?

Builds character? There is a better answer. On this page we have started a collection of papers that consider different ways in which statistical thinking can improve the world. From refuting an exaggerated claim to identifying biased rating scales to collaborating across disciplines to using statistical techniques to enhance critical thinking and / diversity in the workplace - it is worthwhile to examine the ways that we use statistics in our various fields of endeavor.

In this post-factual, post-truth age, it is important to have the skills to separate facts and truth from the distracting fictions that may surround it.

At the moment, the papers cited on this page are those written by your site authors, Profs L & H Friedman.
We will be happy to consider including other relevant research. Please email us with suggestions.

Critical Thinking

The knowledge economy and the digital age have changed the nature of work and management. More people than ever before need to master critical thinking skills to meet employers' demands. This paper proposes a set of 15 scenarios and where they may be used in the context of a one-semester course in statistics. Scenarios are chosen for their relevance, are from the fields of medicine, school admissions, institutional rankings, criminology, business, quality control and pharmaceutical research. Individuals who wish to sharpen their critical thinking skills may benefit from this paper.

Friedman, Hershey H. and Frankel, Martin and Friedman, Linda Weiser, Teaching Statistics with Scenarios to Foster Critical Thinking (January 13, 2016). Available at SSRN: https://ssrn.com/abstract=2715044 or http://dx.doi.org/10.2139/ssrn.2715044

What is Statistical Thinking Good For?

Or, in other words, why do I have to take this class?

You might be wondering, what is statistical thinking good for? Here are some attention-grabbing examples that demonstrate relevance of statistical thinking to all areas of the world we live in. Real-world examples in teaching, evidence-based research, health research, NNT (number needed to treat), happiness research, teacher cheating, attractiveness research, college rankings. The correlation coefficient helps us to evaluate research, i.e., the strength of the relationship reported.

Friedman, Hershey H. and Friedman, Linda Weiser and Amoo, Taiwo, Using Real-World Examples to Enhance the Relevance of the Introductory Statistics Course (August 15, 2012). Available at SSRN: https://ssrn.com/abstract=2129750 or http://dx.doi.org/10.2139/ssrn.2129750

Friedman, Hershey H. and Raphan, Martin, How Statistics Can Save Your Life or End It: A Course Module (December 4, 2013). Available at SSRN: https://ssrn.com/abstract=2363742 or http://dx.doi.org/10.2139/ssrn.2363742

Friedman, Hershey H. and Amoo, Taiwo (2019).The importance of using real-world examples and data to teach correlation. Annual Northeast Decision Sciences Institute (NEDSI) Conference, Philadelphia, PA, April 4-6., Available at SSRN: https://ssrn.com/abstract=3441972

Friedman, Hershey H. and Friedman, Linda Weiser, Reducing the Wait in Waiting-Line Systems: Waiting Line Segmentation (July 1, 1997). Business Horizons, Vol. 40, pp. 54-58, July 1997, Available at SSRN: https://ssrn.com/abstract=909000

Helping people collaborate across disciplines

The most exciting and valuable research is often done at the intersection of two or more disciplines. How can scholars in diverse disciplines using different scientific models, communicate for collaboration? Just think of the Manhattan Project which had experts for a variety of different countries, speaking different languages, and from such areas as math, physics, cryptography, game theory, and management.

Friedman, Linda Weiser, Friedman, Hershey H. and Pollack, Simcha, The Role of Modeling in Scientific Disciplines: A Taxonomy (January 15, 2008). Review of Business, 29(1), pp. 61-67, 2008, Available at SSRN: https://ssrn.com/abstract=2322506

How Statistics can help us to refute or substantiate claims

Before introducing a new drug or other product to the market, companies must test for safety, efficacy and any other claim they might wish to make. Even the nutritional information must be substantiated. Of course, the competition (and government watchdogs) must examine these claims independently. Hypothesis tests might be conducted in order to substantiate a claim a company wants to make or might be used to refute a claim that a competitor is making about its product.

Friedman, Hershey H. and Friedman, Linda Weiser, Substantiating vs. Refuting Claims in Hypothesis Testing: A Course Module (September 2, 2016). Available at SSRN: https://ssrn.com/abstract=2834080 or http://dx.doi.org/10.2139/ssrn.2834080

How to avoid bias in research: What to look out for

Rating scales are used to measure happiness, pain, customer satisfaction, teaching quality, job satisfaction, employee engagement, etcetera - in fact, just about everything. According to Peter Drucker, "What gets measured gets managed.” As informed consumers of statistical research we should be aware of the many ways that rating scales may be biased.

Friedman, Hershey H. and Amoo, Taiwo (1999). "Rating the Rating Scales." Journal of Marketing Management, Winter, 114-123, Available at SSRN: https://ssrn.com/abstract=2333648

Using Statistics for Ethics and Diversity

Some of the most interesting empirical research involves discrimination in the workplace. Some types of discrimination are illegal, others are immoral but not necessarily protected. Subtle forms of discrimination include not hiring people who are unattractive, overweight, short, have speech impediments, have strange names, and/or wear different kinds of clothing. Not all discrimination is overt or conscious. Those who wish to claim discrimination at work will likely have to provide statistical evidence to support their claims.

Friedman, Hershey H. and Leverton, Chaya and Friedman, Linda Weiser, To Foster Creativity and Success, Remove Intentional and Unintentional Discrimination (August 23, 2015). Available at SSRN: https://ssrn.com/abstract=2649712 or http://dx.doi.org/10.2139/ssrn.2649712