Chances Are (22 page)

There is, however, a big difference between accounting and inference, having a list and using it. Double-entry bookkeeping gave Renaissance merchants a way to assess business continuously, gauging the total state of their fortunes as on the day of reckoning; it operates “as if,” creating an instantaneous, fictional balance of assets and liabilities. A similar treatment of social data had to wait until 1662, when John Graunt, draper of London, published his
Natural and Political Observations upon the Bills of Mortality
. In the same decade that mathematical probability arrived, in the work of Pascal, statistics appeared—like its twin planet.

London's weekly Bills of Mortality were an artifact of the city's susceptibility to plague. They were compiled parish by parish and stated how many babies had been christened, how many people had died, and—as far as the authorities could determine—what people had died of. The problems with the Bills of Mortality as a data set were numerous: they covered only members of the Church of England; they listed only burials in parish graveyards; and although they listed an impressive variety of causes of death, from bursting to lethargy, classification was left to ignorant and ill-paid “searchers,” whose diagnostic skill was not even up to the standards of contemporary doctors.

Graunt's simplest goal was to estimate the population of his city: to draw from its mortality an accurate sense of its vitality. He began with the 12,000 recorded christenings every year. Graunt estimated one christening for every two years of a woman's childbearing life, so there should be some 24,000 women of childbearing age. He guessed that there were twice as many married women as childbearing women—so, 48,000 families; and assumed that each family (counting children, servants, and lodgers) would have eight members: London's population was therefore roughly 384,000.

“Estimate,” “guess,” “assume”—these words are never far away in social statistics. The challenge from the very beginning was to find ways to reduce error. Graunt did this using two very modern techniques: sampling and confirmation from unrelated data. He took three representative parishes and actually counted the number of families in them with the numbers of deaths per family, to come up with a ratio of three deaths for eleven families: families/deaths = 11/3. Multiplying the total number of deaths in the Bills of Mortality by 11/3 gave a figure of 47,666 families for the whole city—a good fit to his previous estimate. He also looked at the map and counted the number of families in a 100-yard square in London's most uniformly settled area: the city within the walls. He multiplied his figure of 54 families by the 220 squares in this walled city to get a figure of 11,880 families, then checked the Bills of Mortality to discover that the parishes within the walls accounted for a quarter of all deaths in London. 11,880 × 4 = 47,520. Graunt's estimate fits in three dimensions: he had found a vital way to rid numbers of error by cross-examining them.

Graunt lost his stock-in-trade in the Great Fire, and subsequently became bankrupt, Catholic, and dead in short order—but not before leaving us two further types of information on which great pyramids of industry and speculation have since been built: the mortality table and the odd discrepancy in human births.

Children rarely burst or succumb to lethargy; old people rarely die of thrush, convulsions, or being “Overlaid” by their parents. Distributing these causes of death to their proper ages and assuming a constant rate of risk through life for the expected adult diseases, Graunt devised a table of the number of survivors from a random group of 100 Londoners at ages from 0 to 76. The 64 (only 64!) six-year-olds playing at pitch-and-toss in the narrow street or dawdling to their lessons became the 40 who married at sixteen in their half-built Wren parish church, the 25 who brought their first-born for christening (if it had not been Overlaid), and the 16 who, in the prime of life, ran the shop and business inherited from their parents. By the age of 56, six of them occasionally met at the feasts of their trade or at its elections; three, never the best of friends, remained at 66 to complain about the young, and one at 76 sat by the fire, a pipkin of gruel on his knees, as the lethargy crept upon him.

Graunt's other striking observation was that, year in and year out, more boys are born than girls—about one-thirteenth more—and here, disturbed by something that seemed to contradict the basic coin-toss assumptions of nativity, he went beyond the data to propose a reason:

 

In other words, God in his mercy regulates the birth rate so that Christians need not live like Mohammedans. This argument from Providence persisted for more than a hundred years. It marked an interesting departure from previous ideas of personal experience of the divine: here was an example of God's work that could be revealed only by the collection and analysis of mass fact.

Graunt's more fortunate friend, Sir William Petty, showed what power could follow from a judicious use of data. Shipped for a cabin boy at the age of fourteen, he had been abandoned in Caen after breaking his leg, but soon attracted local help because he could speak Latin and Greek. By the age of twenty-nine, Petty had become a professor of anatomy (famous for reviving “half-hanged” Nan Green) and had patented a letter-copying machine.

When Cromwell's government was carving up a conquered Ireland, Petty went as an expert at surveying—indeed, he was so expert that he returned with an estate of 50,000 acres. It was Petty who realized how valuable calculations like Graunt's could be to the realm: mortality tables could at last reconcile the relative value of an income paid over a lifetime with a cash sum now, or rent on property with purchase price. At a time when most of the kingdom's wealth was fixed in land, this was an essential matter. Petty proposed to Charles II the establishment of a central statistical office that would collect and analyze these vital facts, rationalizing taxes to give the realm a secure income without overburdening its taxpayers. The easy-going monarch chuckled, nodded . . . and no more came of it.

Seventeenth-century governments, almost constantly at war, needed to raise large sums of money quickly, and selling annuities (lifetime income paid in exchange for a single capital sum) seemed an attractive gamble. An annuity buyer is, effectively, betting against his own early death; so a canny government, if possessed of the facts, could offer longer odds than the mortality figures justified, relying on the instinctive belief that everyone dies at an average age—except me. The mathematical apparatus of old-age welfare, of Social Security and private pensions, actually began as an attempt to secure a house edge for the State.

Information about the public, if kept secret, offers private advantage; so social calculation fell into twin wells of concealment: the inner councils of life-insurance companies and the ministries of anxious kingdoms. Throughout the eighteenth century, population and mortality were considered State secrets. The dominant political theory was mercantilism, a form of exalted miserliness that taught that the country with the most gold and most people at the end of the game wins. A sensible monarch would therefore no more reveal his country's population than a poker player would invite opponents to study his cards.

The constant problem was to find a dependable source of raw data: for many years, most scientific assessments of human mortality were based on the experience of one Prussian city, Breslau (now Wrocław), where the Protestant pastors had been bullied into compiling accurate and complete information. Prussia (a country that in this period was spreading across Europe with the stealthy rapidity of a bacterial colony in a Petri dish) encouraged census-taking and internal interpretation, but prevented publication of its results. It was the Prussian professors working on this data who first came up with the term “statistics”—but by this they meant the State's numbers: the vital signs of the realm's health. Prussia knew and numbered every barn and chicken-coop in its territory, but, like a quartermaster's report, this was privileged information.

There were enthusiastic amateur census takers, though. In the 1740s, the Prussian pastor Süssmilch built on Graunt's work: assembling immense amounts of information on births, deaths, and marriages throughout Germany, he found, first that God was clearly punishing sinful city-dwellers with higher death rates; and second, that glimmerings of some mechanism in society could be made out once the mass of facts became sufficiently large. For example, there appeared to be a fluctuating relationship between population and land. More available land meant peasants could marry and set up house earlier, meaning more children, meaning more future peasants, meaning less available land. As economic theory, this may appear very basic—Adam Smith developed far more interesting ideas out of his own head—but the point was that Süssmilch inferred it from
facts
, not from Reason.

Facts had become interesting—not just to government ministers, but to all Germans. There were weekly publications in many towns of whatever lists and numbers contributors had happened to pick up or tabulate. Johann Bernoulli (another one), traveling through Prussian territory, described a princely collection of Old Master paintings simply by their dimensions.

It was a time ready to see itself as the Statistical Age—in as confident and as vague a sense as the Atomic, Jet, or Information Ages would be. Mass, Mechanism, and Number were replacing Nature, Reason, and Proportion as the received ideas of the time. When Quetelet sketched the potential power of his moral physics, the effect was like removing the cork from a shaken bottle of champagne. Mental effervescence fizzed across the continent.

The idea of the simultaneous—many distant others doing things
just at this moment
—arrived with the railroads and their need for uniform time. In the factories, interchangeable parts not only made mass production possible, they changed the products—muskets, ship's tackle, spinning frames—from hand-shaped objects made for the here and now into assemblies of components with potential use at any time or place. Capital was transforming from a solid—my gold in this bag—to the universal fluid of credit. Steam—amorphous, portable, tireless—led industry up from its deep river gorges and made all places equally suitable for a mill. Machine tools, mechanisms to make mechanism, brought in absolute numerical standards of flatness, pitch, and diameter to replace the millwright's personal fit of hand, eye, and material.

Even the nature of numbers was changing: the decimal system tempted us to express proportion as a percentage, giving it the appearance of absolute value. No longer were things “in the relation of one to three” or “two shillings sixpence in the pound” or “and about thus far again”—they were 33 percent, 12.5 percent, 100 percent, precise, uniform subjects of the universal law.

 

Inspired by Quetelet, British scholars founded the Royal Statistical Society, but found themselves caught in a dilemma: was this new discipline a science or just a method that aided other sciences? With a characteristic wariness of Big Ideas, they decided on the latter, choosing as their emblem a sheaf of ripe wheat with the modest motto
aliis exterendum:
“let others thrash it out.” Their first questionnaire,
On the Effect of Education on the Habits of the People
, had as its first question “What is the effect of Education on the habits of the People?”—their technique, luckily, would soon improve.

Statistics were opening the minds of historians and philosophers to the possibility of understanding social mechanics. Alexis de Tocqueville wrote three books that still illuminate the essential distinctions of habit and expectation that separate French, English, and Americans—with not a page of statistics in any of them. When he first saw André-Michel Guerry's essay on the moral statistics of France, accompanied by its beautifully complete returns for sanitation, suicides, and crime, he exclaimed that, were it not for the dishonor, he would willingly be condemned to prison for life if the sentence allowed reading such splendid tabulations.

At once the most extreme and the most ingenious exponent of this new view of history was Henry Thomas Buckle—a meteor that streaked across the skies of fame and is now seen no more. A sickly child, he was indulged in everything by a mother on whom he doted. By the time he reached adulthood, he had acquired fluency in seven languages; a library of 22,000 books; a wide if inconsistent range of knowledge; and two minor vices: cigars and chess.

Buckle had no fear of Big Ideas, and his own was unapologetically vast: that free will, God, and the power of the State were all fictions. The principal, indeed the sole, influences on the development of the human race were Climate, Food, Soil, and the General Aspect of Nature (this last was necessary to explain imagination, poetic feelings, and so on). The differences we might see between us, all the various racial or national distinctions, were straightforward consequences of these mechanical influences.

If humans are simply products of their environments, then, of course, we need to know everything about the environment to know humanity. This was the great use and value of statistics: