Fresh Perspective
Have you ever wondered where the +, −, /, x, and = signs came from? Who invented computing machines? How confidence intervals came to be? The people behind statistical inference methods? Why the census is so critical? How blobbograms save lives?
The history of statistics is about the discovery of secrets (and occasionally lies) that show how the discipline of statistics came about and make it more real and even surprising.
But fun as it is to trot these factoids out at parties (if you are that kind of person), the history of statistics is much more than a collection of trivia. The history of statistics is a history of creative process.
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History provides a fascinating glimpse into human behavior—who the key players were, what they did, and how their activities affected society at large. The history of statistics also has an extra dimension: It provides documented insight into how new and useful statistical ideas are actually generated.
For most of us, the theorems, notations, and even the methodologies we use and take for granted have always been part of our statistical practice landscape. What history shows us is that pioneers in statistics were, above all, creative. They were not always first-rate mathematicians (although many were), but intellectually curious and adaptable; willing to risk failure; and with the talent to identify the true problems, ask the right questions, and synthesize diverse streams of information to find solutions.
Stories from the past also give a fresh perspective on the strategies by which individuals skirted around barriers to their work. Regardless of talent or genius, individuals who create statistical ideas are constrained by their social, political, and cultural environment. Challenges to operating within those constraints were often daunting. Some who “spoke truth to power” were simply destroyed, as was the case for Olimpiy Kvitkin, head of the 1937 Soviet census: He was arrested and executed simply because the results of his census contradicted Stalin’s projections and official lies.
More often, erasures have been subtle. Individuals have been not so much forgotten as overlooked, robbed of credit, denigrated, and attacked, especially if they belonged to an historically excluded group. Discrimination and embrace of “alternative facts” still occur, and remediation attempts still face resistance and even backlash from defenders of the status quo. Knowledge of history provides greater awareness of abuses and disparities, and enables a re-imagining of different strategies for addressing such barriers.
Finally, the history of statistics shows clearly that data does not speak for itself. History shows how beliefs and world views of individual practitioners ultimately went on to influence the supposedly objective interpretation of data and evidence. Ultimately, statistics is a tool for finding solutions to societal problems through transforming data into information, and information into application. However, history shows how both contemporary thought and ideology influenced the practice of statistics, and even perceptions of societal needs.
For example, Quetelet originally conceptualized the “average man” as the normal or ideal. Later, Francis Galton redefined average as “mediocre,” and regarded deviations as indicators of either progress or regression. Galton, with Karl Pearson and R. A. Fisher, revolutionized the theory and practice of statistics, and invented many of the statistical methods used today. However, their work also provided “scientific justification” for many later repressive and cruel policies about intelligence, economic and social disparities, race, and immigration—and even provided support for genocide.
Histories are lost as the cultural zeitgeist changes and collective memory decays. This column will bring back a few of these lost stories of individuals who have been more or less forgotten, but whose ideas have had a profound influence on the daily lives of thousands, if not millions, of people. And of course, the way we practice statistics today.
We are incredibly honored to be asked to serve as editors for CHANCE‘s new “History of Statistics” column. We welcome your submissions and suggestions for future articles.
About the Authors
Penelope Susan “Pen” Reynolds is an applied statistician in the Department of Anesthesiology (College of Medicine) and Department of Small Animal Clinical Sciences (College of Veterinary Medicine) of University of Florida. Her research interests include sample size estimation for preclinical studies and evaluation of statistical quality gaps and their impact on lab animal welfare. Her book A Guide to Sample Size for Animal-based Studies (Wiley-Blackwell) is scheduled for release in September 2023. She was part of the International ARRIVE 2.0 Guidelines Revision Working Group and is a co-author of the ARRIVE 2.0 revised guidelines and ARRIVE 2.0 Explanation and Elaboration document. Reynolds received the 2021 UK Animals in Science-Education Trust 3Rs Prize and—with collaborators Maggie Hull and Elizabeth Nunamaker—the 2022 IQ Consortium and AAALAC International Global 3Rs Award for “significant and innovative contributions to the 3Rs of animal-based research.” She is a published advocate for the improvement of animal-based research through application of statistically based experimental design principles and quality improvement strategies. Her interest in both statistics and the history of statistics began with her grandfather James C. Brady, who was chief of the Institutional Statistics Branch, Dominion Bureau of Statistics (now Statistics Canada), and was reinforced by two childhood books about Florence Nightingale.
Chiatra H. Nagaraja is a senior lecturer in statistics at the University of Exeter in the UK. Her research interests are primarily in measurement, particularly macroeconomic and socioeconomic indicators, time series, and the history of statistics. She combined all three in her book, Measuring Society, a history of U.S. official statistics. Before joining Exeter, she was a faculty member at Fordham University and a research mathematical statistician at the U.S. Census Bureau, where she focused on the American Community Survey. She is currently chair of the American Statistical Association’s Scientific and Public Affairs Advisory Committee, a member of the Royal Statistical Society’s History of Statistics Section, and book review editor for the International Statistical Review. She is also an elected member of the International Statistical Institute.
