One Thing About …
What ignites your passion, feeds your frustration, or impresses you with its beauty or power? What is the “one thing” you want to tell someone, not trained in statistics or data science but interested, about statistics? These are the questions to be answered by this new column, “One thing about…,” which will invite contributors to share their unique perspectives on statistics and data science.
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We will ask potential contributors to consider these questions as they develop their content:
• Is there any way this topic might connect to the lives of non-statisticians? Are there any real-life examples of this statistical or data science “thing” in action? Can we connect this topic to anything people in the public would be familiar with?
• Is there a statistical nugget that non-statisticians might have heard about and always been curious about? Could you imagine saying, “Have you ever wondered why/how/if…”?
• Is there an angle that non-statisticians might find surprising? Is there something that might contradict their prior expectations about the topic? Could you imagine saying, “I bet you didn’t know that…”? For example, people might be surprised to learn that the hot-hand phenomenon is not as simple as it sounds, or that the law of averages is a myth.
In this column, we want to introduce topics (“the one thing”) that both spark curiosity and have the potential to affect daily life. We want the writing to be understandable to someone who may not have taken a statistics class, at least not recently.
In summary, the vision of the ASA asks us to imagine a world that relies on data and statistical thinking to drive discovery and inform decisions. This column will explore topics that, if ignored or misunderstood, will lead to conclusions that are not informed by data and statistical thinking.
“My one thing…”
For the inaugural column, here is my “one thing.”
In the ancient past (also known as “my college days”), the band Blondie had a single—”I know, but I don’t know”—that might be a contender for the statistician’s anthem.
Blondie’s lyrics strike a chord in us, and not just from my off-key car singalong. We prefer certainty. We ask questions of the universe and want definite answers. “Will I need an umbrella today? Can this medicine lower my cholesterol levels? Is it safe for me to take up my dream hobby of knife-juggling while sky-diving?” Frustratingly, life does not present itself in certain terms. “Maybe” and “it depends” are often more accurate answers than “yes” or “no.” They are also far less satisfying.
If I could communicate just one thing about statistics, it would be this: Statistics does not magically get rid of all the uncertainty of life. But it helps us know how certain we reasonably can be.
Statistics does this in two ways: (1) makes answers less uncertain by considering factors that add confusion and (2) gives us a measure of how well we know what we don’t know by providing an entire range of values that are plausible.
For instance, without using statistical methods, we would be limited to asserting that a medicine was effective for most people who participated in a test of that medicine. We would have no basis for concluding how well it would work for anyone else.
That’s useless information. However, a test designed and analyzed using appropriate statistical techniques provides a highly useful estimate of what we want to know: how well the medicine will work for the rest of us who might need it. We go from maximum uncertainty—knowing nothing of value about the effectiveness of the medicine—to a much clearer picture. Uncertainty remains, since we still don’t know precisely how effective it will be for each person, but there is much less of it.
In an uncertain world, statistical methods are ever more important. While statistics doesn’t eliminate the uncertainty, it helps us reduce it and communicate it, so: Sorry, Blondie. It is not a complete mystery. Thanks to statistics, we have a key that will at least unlock the door, giving us a clearer view of the world even amid the uncertainty of everyday life.
What isn’t uncertain is that we want this column to feature diverse voices and topics. If you are interested in sharing your one thing or if there is a topic you would like to see featured, contact us. This is your chance to share that one thing.
About the Author
Ronald L. (Ron) Wasserstein is the executive director of the American Statistical Association (ASA). Wasserstein assumed the ASA’s top staff leadership post in August 2007. In this role, Wasserstein provides executive leadership and management for the association and is responsible for ensuring that the ASA fulfills its mission to promote the practice and profession of statistics.
Before joining the ASA, Wasserstein was a mathematics and statistics department faculty member and administrator at Washburn University from 1984–2007. During his last seven years at the school, he served as vice president for academic affairs.
Wasserstein is a longtime member of the ASA, having joined the association in 1983, and has been active as a volunteer in the ASA for more than 20 years. He twice served as president of the Kansas-Western Missouri Chapter of the ASA and served as chair of two ASA sections: Statistical Education and Statistical Consulting. He also chaired the Council of Chapters Governing Board in 2006 and was a member of the ASA Board of Directors from 2001–2003. Wasserstein is a Fellow of the ASA and the American Association for the Advancement of Science.
