Abstract

Statistics in the Hands of an Angry God?John Graunt’s Observations in Cotton Mather’s New England Ted McCormick (bio) ON August 21, 1708, Ezekiel Cheever, headmaster for thirty-eight years of the Free School in Boston, died at the age of ninety-four. Cotton Mather delivered the funeral sermon. His theme was the shortness of life. In a striking passage, he addressed in the language of numbers the crop of young scholars Cheever had left behind. “Children,” he commanded, “Go unto the Burying-place; There you will see many a Grave shorter than your selves. ’Tis now upon Computation found, That more than half the Children of men Dy before they come to be Seventeen Years of Age.”1 Four years later, while a winter epidemic ravaged Connecticut, Mather again referred his hearers to the cold statistics of political arithmetic: The Extent of Mortality is Universal. . . . They that have made Nice Remarks, on Bills of Mortality, will tell you; That one half of those that are Born, don’t Live Seventeen years: That but about Forty of an hundred, are found Alive, at Sixteen years; That but Ten out of an hundred, at Forty Six; but Six, at Fifty Six; but Three at Sixty-six; but One at Seventy-six. Were there as many Nations, as we are now Entertain’d with Snow-drifts; or as many [End Page 563] Persons as we can see Flakes of Snow; Death, Death will quickly melt them all away.2 In another funeral sermon four years after that, Mather queried the psalmist’s dictum (Psalm 90:10) that “the Days of our Years are three score Years and ten.” He enjoined his parishioners to “form a Computation” of how few would reach that mark when “More than Half the Children of Men, fall so short of Seventy, that it is affirm’d, they die short of Seventeen.” Indeed, he averred, “if the Clerks of our Trained Companies would bring in their Lists, and compare them” with those of twenty years earlier, they would seem “so many Bills of Mortality.”3 Where did these numbers come from, what did they mean to Mather, and what were they doing in his sermons? The first question is the easiest to answer: the source of Mather’s numbers was the “bible” of early quantitative demography, John Graunt’s 1662 Natural and Political Observations . . . upon the Bills of Mortality. Graunt, an enthusiastic adherent of Baconian natural philosophy and the only tradesman among the early Fellows of the Royal Society, had gathered London’s scattered weekly mortality bills and applied his “Shop-Arithmetique” to analyzing the whole.4 His conclusions, offered simultaneously to the state and the community of scientific virtuosi, ranged from the inefficiency of the poor laws to the unhealthiness of London and the unnaturalness of polygamy and celibacy.5 Among the highlights of this “political arithmetic,” however, was a rudimentary table of life expectancy.6 According to this table, making allowances for the fact that “men do not die in exact Proportions, nor in Fractions,” mortality rates remained roughly constant at every given age, from six to seventy-six.7 [End Page 564] Thus Graunt found that of one hundred live births, only about sixty-four would survive past six years, forty past sixteen, and so on. These were the numbers that Mather—a scientific amateur and eventually a Fellow of the Royal Society himself—faithfully repeated. But what did these numbers mean to Mather? What was a life table from Restoration London doing in Boston sermons fifty years later? To date, the only study to answer these questions does so from the point of view of historical demography. According to Daniel Scott Smith and J. David Hacker, Mather and other Congregationalists, grasping the fact that perceptions of mortality influenced behavior, stressed the extreme variation in individual life spans—reinforcing the notion that each life was in God’s hands—and overemphasized the risk of mortality in the short term. This unwitting yet convenient misrepresentation of risk dovetailed neatly with Graunt’s table, which incorrectly assumed a fixed mortality rate for every decade above six years of age, exaggerating the probability of death for...

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