Authors: Oscar Sheynin (Berlin, Germany) and Miodrag Lovric (Radford University, USA)
This comprehensive essay offers a sweeping and detailed exploration of the history of statistics—from its ancient philosophical roots to its modern formulation as a mathematical science. The article opens with an investigation into the etymology of the term "statistics," correcting misconceptions and tracing its first appearance to Girolamo Ghilini’s 1647 work Teatro d’huomini letterati. A blend of linguistic, historical, and scholarly analysis sets the stage for understanding statistics not merely as a discipline but as an evolving concept.
The development of statistics is presented in tandem with the emergence of Staatswissenschaft (the study of the state) in Germany and political arithmetic in England. Landmark contributions by Graunt, Petty, and Leibniz laid the groundwork for population studies and the use of mortality tables. The essay captures how empirical practices gradually merged with probabilistic thinking.
A major section is devoted to the 18th and 19th centuries, highlighting advances by Jakob Bernoulli (law of large numbers), De Moivre (normal distribution), and Bayes (inverse probability). The interplay between chance and divine design, as considered by Laplace and Arbuthnot, is critically examined. The article emphasizes how probabilistic reasoning slowly penetrated astronomy, epidemiology, jurisprudence, and social science.
The contributions of Quetelet, Galton, Pearson, and Fisher are discussed in the context of the Biometric school, which revolutionized anthropometry, correlation, and hypothesis testing. Contrasts are drawn between the British biometric and the Continental (stochastic) traditions, with Chuprov and Slutsky highlighted as mediators seeking synthesis.
The authors document the rise of mathematical statistics, the formalization of estimation theory, and the explosive growth of statistical applications in public health, astronomy, natural sciences, and quality control. The text also chronicles the Soviet experience, where ideological pressures constrained statistical progress, creating a distinct and insular academic environment.
In the final chapters, Sheynin and Lovric reflect on the rise of data visualization, exploratory data analysis, and computational tools, all contributing to a modern statistical worldview grounded in uncertainty, reproducibility, and modeling.
For rare historical findings, biographical insights, and primary source references, consult the full article in the International Encyclopedia of Statistical Science.