Statistics and Eugenics

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Why Statistics Matter

Eugenics is an economic and social idea which stemmed from Darwin’s “survival of the fittest”; however, in eugenics, the “survival” is not quite equivalent to the natural survival described by Darwin. When he hypothesized that the fit would out survive the unfit, he did not have in mind that the fit would be scientifically defined to out survive the other “fit” ones.

When trying to convince a population about a new idea or movement, it helps to have facts to back up what is being asserted. The eugenics movement was about taking Darwin’s idea of evolution and actively applying it to the human race: seeking out the “fit” ones. In the beginning of the eugenics movement, the following people wanted to turn eugenics into a scientifically backed idea which could be implemented in policy. In the attempts to define the humanly “fit” and “unfit”, extensive research took place in search of quantifiable evidence. At this time, statistics was a very new and uncharted science. Much of the work done by the creators of eugenics however turned to mathematically heavy work which would later turn into the foundation of modern day statistics. It was this statistical research and support that eugenics needed to legitimize their cause and to give the human population evidence of their claims. Unfortunately, what the statistical research revealed were flaws in the support of eugenics. Inadvertently however, the failure of statistics to let eugenics succeed led to the advancement of statistics, a science which our world relies on heavily today.

Notable Mathematicians and the Eugenics Movement

Adolphe Quetelet

Before the eugenics movement, there was already statistical application to the natural sciences. It had not been widely applied to the social sciences. Quetelet was regarded as the first social statistician. He was an astronomer and meteorologist. He had an interest however in why people are how they are. He is famous for his creation of the body mass index. [1]

He looked at social situations in a very scientific manner. In physics, there are formulas that will tell you how far something will go if it has an initial velocity of “x”, and angle of “y” and other factors. He applied this to the social sciences. He believed by putting the certain factors into the right equation he could calculate how people should be.

In his research, he created something called the “average man”. This average man was a set of characteristics of a human. He first got the average height and weight of people. He then compared those to sex, age, job and location. This is how he created his average man.

Quetelet was important to the Eugenic movement for two reasons. He was the first one to think that certain factors could determine actions of the average human. It is important to note that these factors were physical. The second reason is a particular quote of his.

“If the average man were ascertained for one nation, he could represent the type of that nation. If he could be ascertained according to the mass of men, he would represent the type of human species altogether.” [2]

The application and belief of this quote is what is troubling and useful for the eugenics movement. The belief that a group of people could be represented as an “average man” is the standard protocol for the eugenics movement.

Francis Galton

Sir Francis Galton was a pioneer and founder of biostatistics and one of its intellectual leaders and financial supporters. Even though the beginning of his career consisted of work in the likes of geology, meteorology, and geography, it was the introduction of eugenic thought which fueled his greatest and most influential work. An important relative and scientific contact was his half-cousin Charles Darwin. The work of Francis Galton as it turns out was driven more by his political and social motives than it was driven by the advancement of his mathematical research.

Galton pursued statistics because he saw it as the answer to the questions of heredity, which once answered, would solve the social and political problems he thought plagued the race of men. He sincerely believed that statistics would build the perfect eugenic state. This comes as no surprise since many accounts of Galton from an early age describe him as “rarely taking a walk or attending a meeting without counting or enumerating something” (Kevles 8). Despite the fact that he wasn’t as much of a sophisticated mathematical scholar compared to the mathematicians of his time, his thought processes were always driven by numbers.

After reading Darwin’s The Origin of Species, Galton was convinced that studying heredity would produce a way of improving mankind, and that over time we could breed intelligence much as species of animals are bred for survival. Galton hoped that statistically proving the laws of heredity, and importantly with human heredity, that there would be a basis for political and social reform. He envisioned a society where eugenic values were supreme. It was Galton’s political drive and social agenda which led to his discovery of regression and correlation.

In Galton’s early publication Hereditary Genius he modeled the estimated male population of England to create an intelligence curve which using the calculus of probabilities he could predict just how many people would fall into the each section of intelligence. Galton’s incomplete mathematical background however depended on the work of other mathematicians such as Quetelet and others to truly understand what was mathematically achievable.

An important failure in Galton’s studies is of particular note. Galton was convinced that binomial expansions were the basis of his hereditary model and not that of the normal curve. The binomial curve represents a finite number of definable causes whereas the normal model represents an infinite number of definable causes. Here we see that Galton was opting for heredity over environment. Environmental factors are infinite and with Galton’s incorrect model, he claims nature of nurture. This shows his overriding concern with the eugenic ideal, namely that environment does not much affect the character of men. He hoped that a binomial model of heredity would restrict the number of genetic determinants thus implying that environmental factors are negligible. Although Galton was wrong in these assertions, it proves his dedication to his political and social desires.

Galton realized that he needed to do some serious statistical analysis to find what he was looking for in his quest to figure out heredity. His first two notable experiments were the collection of school boy heights and sweat pea parent/progeny measurements. He spent a lot of time analyzing the heights of boys until he realized that what he really needed was data of different generations. The easiest way for him to do that was to grow sweat peas. He sent out seven batches of peas to friends and asked them to grow them and send their progenies back to him for measurements. From this data he could analyze the measurements of a spawned generation. He gained two important facts from his data: (1) the offspring of extreme plants are closer to the population mean than their parents are, and (2) one degree of variation, one statistical unit, is the same absolute measurement whether the offspring of extreme parents or the offspring of normal parents are considered

Graphing parental seed size on one axis and offspring size on the other, he plotted wherever the parental size and mean offspring size intersected. Connecting marks into a straight line of calculable slope, he had drawn the first regression line and had calculated the first regression coefficient. Galton had found that the measurements of the offspring tended towards the mean of the population. From further statistical work he came upon the coefficient of correlation. This number would show how two things related even if they had nothing to do with the hereditary process or even held the same units. Correlation is again an important concept in modern day statistics.

Through his pea experiments he realized that if he wanted to make progress with his political and social motives, then he would need to do statistical analyses of human progenies. This led to the start of his anthropometric laboratory. He established this laboratory for people to come have measurements taken which for a three pence entrance fee, the testee would get to keep a copy of Galton’s results. Subjects were measured on different physical and functional dimensions including many physical body measurements in addition to things such as strength, breathing capacity, eyesight, and more.

Galton’s anthropometric data gave him much more material to statistically analyze in hopes to support the cause of eugenics. Unfortunately, Galton repeatedly found that most characteristics tended towards the mean. His statistical findings were not the clear cut answers to eugenics as he had hoped. On the flip side, his discoveries led to two of the most important mathematical concepts of modern day statistics. Regression and correlation were monumentally important and these ideas were founded on Galton’s interest in heredity. He created biostatistics in a pursuit of an answer to the problem of heredity. His dream was that of a truly eugenic society which was based upon the laws of heredity. He believed these laws would guide the breeding of mankind and the evolutionary welfare of the race would become a moral criterion (Cowan 527).

Karl Pearson

Pearson was one of the very first creators of modern statistics. His work directly followed that of Francis Galton. Pearson began his early work on studying whether characteristics were directly passed down from parent to child. He ran experiments that tried to discover if mental aptitude was passed down from parent to child. Because it would take too many years to test a parent against a child, he decided to test siblings and find if there were notable differences between them. Through this test he came to the conclusion that mental aptitude as well as all characteristic traits were passed down from parent to child.

This “discovery” by Pearson led him to believe that it was possible to breed a superior race of humans. Pearson believed that their was a war to wage on inferior races and that England was in a state of deterioration. He was a large proponent of the idea that the upper class needed to reproduce more as the nation was becoming more unfit from the vast reproduction of the lower class. He attempted to prove this idea by creating his own new science he called biometry. This was essentially a science that proved things about biology through statistics. Pearson did come to many conclusions with this new science many of his conclusions are now disregarded as there was immense bias towards the eugenics side.

Although Pearson’s use of statistics were clearly involved in proving his theory of superior races he did come up with many topics that are still used today. His contributions include linear regression, correlation, the correlation coefficient, and the chi square goodness of fit test. All of these contributions are still used today and taught in universities and colleges around the world.

R.A. Fisher

R.A. Fisher is another notable statistician who believed in eugenics. Fisher was also a notable geneticist as well. He once wrote a paper entitled “The Correlation Between Relatives on the Supposition of Mendelian Inheritance.” This paper tackled a eugenics issue that involved both genetics and statistics. Fisher believed that the genes of the parents would be passed on to their children. In this paper he introduced new statistics that included the idea of analysis of variance (ANOVA). ANOVA has become a well known and commonly used statistical test to measure correlation between multiple objects. Fisher believed that the intelligence of a person was directly passed down from their parents. Fisher also believed that one could predict how many children a woman would be able to have by the amount of children her parents had.

In Fisher’s case he took this belief a step further. He actually attempted to create a family based on his eugenics beliefs. He ended up marrying his wife based off of the fact that she was one of 10 children and that her father was a very well known man of faith as well as the fact that his family, the Guinness family was known around the world for not only the religion side, but also that of the brewing side and a family of well known bankers. For Fisher this could not have been a better eugenic marriage. He had a wife that would be able to have many children but also was from a well off family known for its intelligence in multiple different ventures. Fisher was known to believe that the upper class needed to have large families in order for them to cancel out the lower classes continued growth of “lesser people.” Although he was able to create a large family, he and his wife had 9 children, their marriage would not last as his wife was unable to cope with his drastic beliefs.

Even through this all he never stopped believing in eugenics. In 1933 he became a professor of Eugenics at University College London. He eventually received the honor of Knight Bachelor from Queen Elizabeth II in 1952 for his work in genetics and statistics, which were quite profound as he did create ANOVA and what became to be known as biometrical genetics, but obviously his eugenics background was overlooked. To leave a lasting impression of what Fisher truly believed about people of the world here is a quote about how he thought races differed: “(they differ) in their innate capacity for intellectual and emotional development.” [3]

William Farr

William Farr was another member of the British scientific movement into eugenics. Farr’s expertise were in the medicinal statistics. He was one of the first people to view each human as a single “unit.” That is each person could be regarded as a single organism in a larger social organism, the entire population. This is similar to Adolphe Quetelet’s average man idea.

This idea was important to the eugenic movement as he believed that you could target classes of inferior people, such as the criminal class in England, and essentially fix them or remove them from the greater population. The following quote of his sums up his argument:

“If by any judicious means the increase of the incurably criminal, idle, insane, idiotic, or unhappily organized parts of the population can be without cruelty repressed, under a system of religious discipline, to a greater extent than it is at present by the selection that pervades, more or less, the whole system of English marriages,—the character and qualities of the race will be immeasurably improved.”[4]


The “average man” that Quetelet talks about seems feasible when talking about physical characteristics. This being said, it is an average physical body given the same backgrounds. For example, a malnourished person isn’t going to have the same weight or development as a person with a balanced diet. It happens to be that there are populations in the world where many people have good diets and others lack proper diets. This could make it seem that there is an “average man” in a third world country and an “average man” in the United States. However, this average man in the US has a higher average because of availability to a sufficient diet.

This sufficient diet is a variable in creating an average human. This example is used to move to a less clear example of intelligence. The eugenists believed that there were populations that were more intelligent. They would use tests to gather statistics on the people. These test do not take into consideration social variables, just like a proper diet would not be considered when defining the “average man”.

In response Pearson and Fisher would say that selective breeding would be a more efficient way to improve the society. This is obviously inhumane and not true. Many of these mathematicians actually rose from a more humble beginning such as R.A. Fisher, and thus proving that there are great minds in the lower classes that just need the opportunity to use them. No statistical test that these men created can prove that people who begin in the lower class are naturally less intelligent because they don't take into account the social factors as discussed above.

Modern Application of Statistics

Social statistics are not a thing of the past. They are used in economics to figure out how different populations are being either hurt or helped by certain factors. Unlike in the Eugenics days, the findings of statistics are interpreted. The cause of the results are not “they are Irish”. Today, the cause could be they are not educated enough, that is why they aren’t scoring well. This is in contrast to the "they are not scoring well because they are dumb as a result of biology" eugenic idea.

Human Development Index

“Human development is the enlarging of people’s choices”. The HDI is used by people around the world to measure similarities and differences between people. The HDI has different categories to measure the people of different nations. For example, there is a section with “adult literacy rate” and there is a section called “public expenditure on education”.

In Portugal, the adult literacy rate in 2005 was 93.8%. In Nepal, it was 48.6% in 2005. In the Eugenics days these statistics would lead the them to say the people of Nepal are not as smart as the ones in Portugal. However, these numbers are looked at in a different way. With HDI, the one reviewing the statistics would look at other factors that could be the cause of this. In Portugal, 5.7% of the GDP was spent on education. In Nepal, 3.4% of the GDP was spent on education. The difference spending priority could be one reason for the difference in literacy rates.

The focus of the HDI is to give a variety of statistics about the people of the nations. They are to be used to try to understand how to improve the lives of the residents of those countries. Unlike eugenics, these statistics aren’t saying that "x %" of the residents of the counties only have the ability to be literate. They are saying that there are “x” many people are literate and there are other factors that make up the citizens of the country.


Obesity statistics are also widely used. Rarely is the topic of obesity discussed as a problem of biology. Rather, obesity is discussed as a social and economic issue. A report points towards southern US states as having higher obesity rates. It says that a national average of 26% of the population is obese, while there are counties that are nearly 44% obese.[5] Eugenicist would say that the counties with these high obesity rates are fat by nature while a modern day sociologist or economist would point to other factors which cause the obesity.


Waller, John. "Ideas of heredity, reproduction and eugenics in Britain, 1800–1875." Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. Volume 32, Issue 3, September 2001, Pages 457-489.

Moore, James. "R.A. Fisher: a Faith Fit for Eugenics." Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences. Volume 38, Issue 1, March 2007, Pages 110-135.

Kevles, Daniel J. In the Name of Eugenics. Pages 3-40.

Cowan, Ruth Schwartz. "Francis Galton's Statistical Ideas: The Influence of Eugenics". Isis, Vol. 63, No. 4 (Dec., 1972), pp. 509-528. The University of Chicago Press.

Johnson et al. "Galton's Data a Century Later". August 1985. American Psychologist. pg. 877-895.