Statistical Physics and Thermodynamics
Thermodynamics emerged during the Industrial Revolution with heat engines being used as a model for making more and more efficient machinery. Statistical physics emerged about a century later, looking into microscopic properties in favour of thermodynamics and the macroscopic. Although statistical physics itself has some diverse history in terms of those who studied it, the statistical distributions used often have less innocent origins.
Probability, Distribution and Arrangement
Satyendra Bose - developed Bose-Einstein statistics and Bose condensate
Heat Transfer and Temperature
Kirstine Meyer - discovered the concept of temperature
The Origins of Thermodynamics
Newtonian mechanics quickly spread across the West in the build-up to the Industrial Revolution. In 1712, Thomas Newcomen invented the first steam engine which was later improved upon by James Watt in 1769, using calculations concerning the Newcomen engine’s efficiency. These steam engines were almost immediately adopted for industrial profit. Mines, factories, locomotives, and much more made use of the potential that steam engines could generate. Of course, these steam engines fall more into the realm of mechanical engineering, but the influence of Newton describing his laws of motion in 1687 paved the way for such developments and (arguably) the creation of thermodynamics with Sadi Carnot’s theoretical model of the Carnot cycle at the turn of the 19th century: kickstarting a new area of physics.
The Influence of Eugenics on Modern Statistics
Modern statistics can be traced directly back to Europe in the 16th and 17th century with the newly emerging field of probability theory. This is the birthplace of modern statistics: statistics as we know it today. Evolving from probability theory into the uses of continuous distributions used to extrapolate data around the later 18th and early 19th centuries, we now begin to really see the concepts of statistics which are used in physicists’ data analysis toolkits today. Error and regression analysis also emerged in this time, but unfortunately these were not overall developed for innocent means. Around this time, ideas surrounding eugenics and social Darwinism were rapidly rising in popularity and they almost entirely fused together with statistics, becoming a single subject. At the turn of the 20th century, common measures such as correlation and standard deviation began to emerge. Immediately, eugenicists were using — if not discovering — these concepts to perform ‘scientific racism’ in an attempt to prove intellectual and physical inferiority of disabled persons and the ‘non-white race’.
Statistics and eugenics would remain almost inseparable for another few decades, culminating in the Nazi’s ‘research’ during World War II and the Holocaust/Aktion T4. Fortunately, however, the popularity of eugenics saw a sharp decline in post-war Europe. Despite the fact that many British statisticians of the era would continue praise for the eugenics work of the Nazi’s, statistics was finally able to diverge itself for the most part and become its own field again. Perhaps due to this sharp decline, many forgot about the dark legacy of statistics. Research journals founded by eugenicists simply renamed themselves and did not recognise their history for many more years. This brief history of developments ultimately forms the data analysis toolkit taught across the whole of physics today.
Sources
Louçã, F. (2009). Emancipation Through Interaction – How Eugenics and Statistics Converged and Diverged. Journal of the History of Biology, 42(4), 649–684.
Nye, R. (1993). The rise and fall of the Eugenics empire: recent perspectives on the impact of biomedical thought in modern society. The Historical Journal, 36(3), 687–700
Further reading
Gould, S. J. (1996). The Mismeasurement of Man (2nd ed.). Norton.
Saini, A. (2019). Superior: The Return of Race Science. UK, Beacon Press.
Stigler, S. (1986). The History of Statistics: The Measurement of Uncertainty Before 1900. Harvard University Press.