In The Rise of Statistical Thinking, 1820 – 1900, Theodore M. Porter argues, “The doctrine that order is to be found in large numbers is the leitmotif of nineteenth-century statistical thinking. The regularity of crime, suicide, and marriage when considered in the mass was invoked repeatedly to justify the application of statistical methods to problems in biology, physics, and economics” (pg. 6). He continues, “The use of probability relationships to model real variation in natural phenomena was initially made possible by the recognition of analogies between the objects of these sciences and those of social statistics” (pg. 6). Porter further argues, “The history of statistics sheds light on the relations between abstract science and what are often seen as its applications. In truth, practice was decidedly ahead of theory during the early history of statistics, and ‘pure’ or abstract statistics was the offspring, not the parent, of its applications” (pg. 10).
Porter writes, “Implicit in the use by political arithmeticians of social numbers was the belief that the wealth and strength of the state depended strongly on the number and character of its subjects” (pg. 19). Further, Porter links statistics to the rise of modern bureaucracy, writing, “The information that numbers could provide was vital for controlling the population, and especially for augmenting tax revenue. More fundamentally, however, the ideal of enumeration was one which few other than agents of the crown would seriously have entertained, at least on the Continent, under the Old Regime – and monarchs typically regarded demographic figures as a state secret, too sensitive to publish” as it might eliminate the basis of social hierarchies (pg. 25). Porter writes,
“Until the nineteenth century, then, statistical regularity was generally seen as pertaining to the natural history of man, and as indicating divine wisdom and planning. The first well-publicized instance of statistical order which could not be plausibly interpreted in this way was Laplace’s announcement in the Philosophical Essay on Probabilities that the number of dead letters in the Paris postal system was constant from year to year. The uniformity of murder, theft, and suicide was even more difficult to explain in natural-theological terms. Quetelet was, in some sense, able to do so, but only by embracing a cosmology at once physicalist and theological that made mass regularity the expected outcome of natural processes in every domain” (pg. 51).
While this would seem to question free will, Porter describes Buckle as working out a compromise position.
Porter writes, “The mathematics of variation was instrumental for the impressive achievements of the nineteenth-century kinetic theory, including Boltzmann’s reduction of the second law of thermodynamics to mechanics and probability theory. It also provided the key in biology to the quantitative study of heredity, leading eventually to what is now the most purely statistical of the natural sciences, quantitative genetics. Beyond its importance for particular natural and social sciences, however, the new understanding of the error law that derived from Quetelet’s work proved essential for mathematical statistics itself” (pg. 110). He continues, “The theory of evolution by natural selection provided the context in which statistical biology was introduced, and within which it has since been most fruitfully developed” (pg. 134). Porter further writes, “Statistical determinism became untenable precisely when social thinkers who used numbers became unwilling to overlook the diversity of the component individuals in society, and hence denied that regularities in the collective society could justify any particular conclusions about its members” (pg. 151). In this way, “Blind use of averages threatened to supplant that je ne sais quoi, medical tact, upon which physicians prided themselves. Accordingly, the so-called numerical method in medicine was viewed by many with suspicion, and subjected on occasion to vitriolic attacks” (pg. 157).
Finally, Porter writes, “The stimulus for a successful mathematical statistics came less from the theory of errors of observation than from the use of probability distribution formulas to model real events in nature and society. Its beginnings are to be found in the last quarter of the nineteenth century, partly in Germany, where probabilistic analysis was first applied constructively to statistical social science between 1875 and 1880, but primarily in Great Britain” (pg. 232). ( )