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“Adolphe Quetelet: Statistics and Social Science in the Early 19 th Century” Evan Brott February 3, 2003
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Quetelet: 1796-1874 Today, Quetelet is nearly unknown But, he made major contributions to statistics Also one of his era’s greatest social scientists
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Main Works 1835- Publishes Physique Sociale: A Treatise on Man, and the Development of His Faculties which introduces the concept of the ‘Average Man,’ a basic concept in the Social Sciences. (That’s him on the right) 1846 – Is the first to fit a normal curve to a distribution of human traits
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Outline 1)Science in the 1830’s 2)The Early Life of Quetelet 3)The Average Man: a Study of Mortality 4)Comparisons of Average Men: a Look at European Sex Ratios 5)Statistical Morality and Early ANOVA: Crime and Punishment in 1820’s France 6)Fitting a Normal Curve: the Chest Size of a Scotsman 7)Quetelet’s Legacy
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Part I: Science in the 1830’s or: They Thought WHAT!?
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State of the Arts Quetelet’s research was from 1820-1850. MANY theories we take for granted were not yet developed.
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Biology 1859 – Darwin publishes The Origin of Species 1860s – Pasteur develops Germ Theory of Disease 1865 – Mendel discovers basics of Genetics
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Quetelet’s Environment Spontaneous Generation not disproved Quetelet believes Miasmic Theory of Disease Many results seemed strange without understanding heredity
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Social Science Quetelet one of the first mathematical social scientists 1830’s beliefs seem very strange today Ex: Phrenology: Personality read by the shape of the skull
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Early Statistical History Beginnings in 17 th century Studied Laws of Probability through Gambling
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More Proto-Statistics 1680s: Newton and Leibniz independently develop Theory of Calculus 1689: Bernoulli first states the Law of Large Numbers
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Normal Distribution 1733: De Moivre finds Normal Distribution arises as a limit of the Binomial 1778-1812: Laplace develops the Central Limit Theorem 1809: Gauss finds that most random errors are distributed normally
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Future Statistical Knowledge 1890s: Pearson develops his correlation coefficient 1904: Gosset (a.k.a. ‘Student’) develops the t-distribution 1920s: Fischer’s work starts the modern era of statistics
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Part II: The Early Life of Quetelet or: how to build an observatory without really trying
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Origins Born on 2/22/1796 in Ghent, Belgium Doctorate in conic sections from University of Ghent in 1819
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Astronomy Initial post-doctoral work in astronomy under Arago and Bouvard Famous story about founding Belgium’s first observatory: traveled to France at age 26, and got funding despite having NO experience at all.
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Astronomical Statistics Galileo first showed astronomical measurement errors were: - random - symmetric - small errors occur more often than large errors.
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Hypothesized Error Distributions Thomas Simpson (1756) Daniel Bernoulli (1777) Karl Freidrich Gauss (1809)
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More Statistical Exposure Met the 75-year old Laplace while getting funding for his observatory Post-doctoral mathematical work with Fourier
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The Census 1826: began work with the Belgian Department of the Census- was in charge by 1829. All censuses at that time were total population counts; Laplace thought of a simpler method Count the number of births in several regions; then multiply by ratio of births/population
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Quetelet’s Plan Quetelet was interested in Laplace’s method Received a letter from Baron de Keverberg Letter said far too many variables in social science for random sampling Quetelet was convinced- conducted full census anyway
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PART III: THE AVERAGE MAN
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Physique Sociale Newton’s mechanical physics was highly esteemed in Quetelet’s time Quetelet envisioned a similar Social Physics Central to this was the idea of The Average Man – which was likened to a social ‘center of gravity’
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What is the Average Man? It’s exactly what you think it is Consider human size: Small AVERAGE Large
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Influential Quetelet was obviously not the first to think of this sort of thing He popularized it, and as we will see carried the concept much further though It is a VERY common concept today
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Nutritional Example “The average man needs 250g of carbohydrates each day”
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Common Example “The Average Family has 2.4 Children” (Here, we see the Average man doesn’t necessarily exist)
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-“The Average American will save $278 dollars with my tax plan” -“But 50% goes to the top 1% of Americans” -“The bottom 20% pays no taxes” -“The top 1% makes over $300,000 already” - And so on... Political Example
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Silly Example “The Average Man has less than 2 legs” (Out of the worlds 6 billion people at least 10,000 have only 1 leg...)
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What Quetelet Thought “If an individual at any given epoch of society possessed all the qualities of the average man, he would represent all that is great, good, or beautiful.”
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Cournot’s Critique “A totally average man, if forced to exist, would be an unviable monstrosity: just as the averages of several different right triangles will not be a right triangle.”
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Quetelet’s First Example The beginnings of Survival Analysis came from Mortality Tables These listed the expected times of death In short, the Age of the Average Man
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Quetelet’s Work Mortality- P(dying this year)*10,000 Viability- 1/P(dying this year)
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Part IV: Many Average Men Or:Where Male Babies Come From
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Categories Quetelet did not only envision the Average Man as a ‘global average’ Rather, there was: An Average Man – and Woman – for every “race, location, age, and epoch – and all combinations of these” Allowed between group comparisons
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Categories This was also understood before his time The mortality tables were divided by gender, location, and occupation Still, Quetelet popularized and greatly refined the notion
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It is a biological fact that 1.06 male babies are born for every female baby. Known as early as the 17 th Century Why? 1.06 : 1.00 The Sex Ratio
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Current Thought Evolutionary: men are more expendable Sources of variation: - Prenatal diseases disproportionately effect boys - First birth, younger women have more boys - Effects of family planning Quetelet noticed most of these!
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The Mind of God 1710: John Aurbuthnot believes probability evidences the Divine Mind: Sees sex ratio as evidence – more men die in war, but still enough left to evenly match with women One of the first applications of probability outside of pure math / gaming
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Quetelet: by Country Shows global average; evidence of variation
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Sources of Variation Tried to explain why different countries had different ratios Decided on racial differences (e.g. Russians naturally have more boys than Swedes) Showed many other possible causes
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South Africa Climate, Race, Lifestyle, Small Samples
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Legitimacy The following page shows a table of births by marital status Quetelet never said WHY this effect was there – surely he didn’t think church sanction ‘blessed’ the couple with more boys? Proxy for age? Or social status?
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Legitimacy
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Age Quetelet presented other theories, this one from Hofacker: Overstates effect
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Other Theories Dismisses Bicke’s family planning theory Shows first marriages (not births) lead to more boys Town vs. Country also considered Decides on Race
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Still Births Several Chapters later, demonstrates that Stillbirths are predominately male Does not realize that differing levels of healthcare can exaggerate this effect- accounting for variation
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Part V: Analysis of Crime or: “If you must murder, try to be a well- educated woman over 30”
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Victorian STAT 410 Ordinary Least Squares had been known for centuries ‘Regression’ would not be called such until Galton in the 1870’s Hypothesis Testing, ANOVA still in extremely vague state
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Criminology Data collected from the French Courts of Assize from 1825-1830 Avg. Probability of Conviction: 0.614
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Question P(conviction) = 0.614 for THE average man. Is this probability different for different groups of people (different “ average ‘men’ ”)?
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Answer: YES!
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New Question: How can we Explain this Variation? From the table, it appears that gender, age, type of crime, appearance at trial, and educational status are important. How can we tell which of these are significantly different from 0.614? Which of these variations are more significant than the yearly variation? Can we make multiple comparisons?
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Quetelet’s Paradigm 3 sources of variation - Constant (e.g. women always have a lower rate) - Variable (e.g. conviction rate decreases w/ time) - Accidental (e.g. a change in alcohol policy at the university causes more arrests, but not convictions, in 1828.)
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Analysis of Variation
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Relative Degree of Influence Calculated as For instance- for crimes against property we get |0.655-0.614|/0.614 = 0.067 Thus, property crimes are ‘average crimes’
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How to Assess Variability without knowledge of 2 Quetelet used (x max -x avg )/x avg and (x avg -x min )/x avg to give limits on variability. Hence for superior education we get a range of (0.40-0.35)/0.40 = 0.125 and (0.48-0.40)/0.40 = 0.200
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What does all this mean? Higher ‘relative degree of influence’ means the cause is more likely to be constant, i.e. P(conviction|status) P(conviction) If ‘variability’ is less than R.D.I., then variation by year (variable cause) is less important than the constant cause
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Example: No Shows Average Conviction Rate = 0.960 Relative Degree of Influence = 0.563 Lower Variability = 0.031 Upper Variability = 0.010 High RDI -> significant Small variability -> same across years
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Comparisons Can we compare groups’ conviction rates? No, not really. We have a very poor grasp on variability, and cannot conduct hypothesis testing. Nevertheless, Quetelet states that the best position to be in was “a well-educated female over thirty, appearing voluntarily to answer a crime against persons.”
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Primitive ANOVA Can we decide which causes are more variable or influential? Well, sort of. Quetelet has the basic framework of ANOVA set up Lacks consistency and optimality properties; ANOVA will be refined by Fischer in early 20 th century
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Multiple Comparisons Many data groupings highly dependent (e.g. gender and higher education in the 1820’s) Basic, modern ANOVA would fail in these circumstances too! So the ‘well-educated, voluntarily appearing woman over 30’ comment is not valid
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Poisson Quetelet’s most famous contemporary (by today’s standards, anyway) was Poisson. Poisson also analyzed this same dataset Summary: - Using corrected data for 1825, refutes Quetelet’s claim of decreasing rates - Modeling jury selections as a binomial random variable, gets a rate distribution - Comes up with pseudo-Bayesian probabilities on conviction.
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Part VI: Fitting a Normal Curve or: Statistics and the 48-inch chest
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What is Normally Distributed? Laplace’s CLT (1778-1812) showed that the Normal is the limit of many distributions Gauss (1809) shows it is a very common error distribution Quetelet is the first to show human physiology can be normally distributed Thinks ALL natural variables are normal
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Scottish Army Uniforms in 1819 Data on the following page collected by Scottish army Needed to fit shirts to soldiers – so tried to estimate soldier’s shirt sizes
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Average Soldier? Can’t just clothe the ‘Average Soldier’ – gotta clothe ‘em all. Possibility – Average solider of each height
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1846 Instead, decides to fit a normal curve to his data. Did not have a normal table – used a binomial with n=999 (1,000 outcomes) Created a table by realizing y n+1 = y n * (999-n)/(n+1) for the binomial
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Odd fit 1) Split data at median 2) Find upper/lower cumulative frequencies 3) Transform to rank scale through inverse binomial 4) ‘Match ranks to transformed ranks through trial and error’ (???) 5) Transform fitted ranks through inverse normal.
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Influence This gave Quetelet mathematical justification for the average man He asks: can we tell the difference between these measurements, and very inaccurate measurements on a single soldier? Normal can only arise through Accidental causes: All is NORMAL!
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Part VII: Quetelet’s Fallout or: The Good, the Bad, and the Statistical
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Francis Galton (1822-1911) Primary work in the 1870s Discovered Genetics independently of Mendel Coined the phrase ‘regression to the mean’ Developed several intelligence tests Mentor to Karl Pearson; Cousin to Darwin Found direct precursor to Pearson’s r 2 Often considered the father of social science Often mistakenly credited for Quetelet’s work on the Normal
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Theory of Heredity Firmly believed that performance was based solely on genetics Severely discounted education/life experience Concerned with intelligence, strength and beauty- thought all were dependent on each other
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Fallacy Armed with: - his belief in heredity - Darwin’s theory of evolution - Quetelet’s many Average Men Reached startling conclusion: groups of people can be mathematically shown to be inferior to others!
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Eugenics Therefore, we must ‘improve the human stock’ Galton’s methods: - encourage matings between desirable people - forced sterilization of the truly unfit (criminals, the insane, etc.) Science largely accepted in late 19 th century England Pearson was Chair of Eugenics at Oxford!
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Theory to Practice Most infamously adopted in Germany, 1930-1945 Justified concept of ‘Aryan Master Race’ Sterilization upgraded to genocide Obviously, today Eugenics is widely condemned Galton’s Eugenics merely ‘bad’, not ‘monstrous’
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Quetelet’s Fault? Made few value judgments in comparison (e.g. only found one highly qualified mention of racial intelligence) Considered the Average Man to be ‘beautiful,’ not ‘mediocre’ Advocated social reform (education, increased government spending) – not the gradual breeding out of the inferiors That is: NO!!!
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Florence Nightingale (1820-1910) Studied statistics extensively under her friends Quetelet and William Farr Strong believer that statistics was evidence of the Divine Mind: Statistics was her religion Worked extensively in wartime hospitals, saving many lives Used statistics to do so!
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Hospital Sanitation Germ Theory of disease not understood Hospitals – especially at war – lacked even basic methods of sterilization Demonstrated that Dr. Lister’s antiseptic surgical implements saved many lives- using Quetelet’s statistical methods
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Eulogy for Quetelet “Quetelet has shown us the path we must go on if we are to discover the laws of the Divine Government of the Moral World.” “It is not understood that human actions are – not subordinate, but – reducible to general laws... Of these at present, we know hardly any. Our object in life is to ascertain what they are.” “A fitting memorial to Quetelet would therefore be the introduction of his science in the studies of Oxford”.
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Overview of Quetelet’s Statistical Contributions Did much to firmly establish statistics as a reputable science, and to mathematicize the Social Sciences The Average Man is an enduring paradigm for statistical and social reasoning Showed basics of data analysis, hypothesis testing, and analysis of variance Demonstrated that natural human traits are normally distributed
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THE END
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