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By Root 872 0

it’s hard for us to imagine that a number can be made to lie. Even the oafish Joe McCarthy knew this; when he declared that 205 communists had infiltrated the State Department, his outrageous falsehood was given the appearance of absolute fact. But proofiness is not merely a tool for propaganda as it was for McCarthy—it is much more dangerous than that. Democracy is a system of government based upon numbers, and rotten numbers are eroding the entire edifice from within. Proofiness in America is used to disenfranchise voters and to bias elections. It’s used to drain money from our treasury and put it in the pockets of unscrupulous businessmen. Proofiness tilts the scales of justice and helps condemn the innocent. It puts lies in the mouths of reporters. There’s no institution in a democracy that’s immune.

The only antidote to proofiness is, ironically, mathematics. Numbers can shatter myths and can disprove falsehoods. They can be turned against their abusers. They can banish proofiness—or at least reduce its influence.

The understanding that real-world numbers come from imperfect measurements can inoculate you against Potemkin numbers, disestimation, and fruit-packing—it imparts a skepticism about where numbers come from, whether they’re trustworthy, and whether they’ve been presented in an honest and straightforward manner. A little mathematical sophistication—and a little practice—allows you to recognize errors of randumbness, causuistry, and regression to the moon; once you get used to spotting phony patterns and false connections, you’ll begin to see them everywhere. You’ll see how advertisers pump up their products, how bureaucrats cover their failing projects, and how would-be prophets convince the unwary to believe meaningless predictions. And while mathematical knowledge won’t stop businesses from ruining the economy, politicians from stealing elections, and court officers from undermining our justice system, it will prevent the malefactors from getting away unobserved.

Mathematical sophistication is the only antidote to proofiness, and our degree of knowledge will determine whether we succumb to proofiness or fight against it. It’s more than mere rhetoric; our democracy may well rise or fall by the numbers.

Acknowledgments

My most heartfelt gratitude goes to my editor, Wendy Wolf, my copyeditors, Don Homolka and Roland Ottewell, and my agents, Katinka Matson and John Brockman—without their careful shepherding from idea to manuscript to final proofs, I would never have been able to complete this book.

Thanks to my colleagues at NYU, who have been wonderful to me. Particular thanks go to Pete Hamill for discussions about Vietnam, but also to the other members of the journalism faculty, as well as to the deans who give us the freedom and the support to pursue our interests.

Most important, I am thankful for the love of my family: my parents, my brother, and my wife Meridith—and, last, but not least, my new daughter, Eliza Rose, who gave an author the best incentive ever to meet a deadline.

Appendix A: Statistical Error

Imagine that you’re a pollster. It’s October 2000—a very exciting time to be conducting polls, because the race between Bush and Gore is neck and neck. You don’t know this (after all, you haven’t conducted your poll yet), but the country happens to be exactly evenly divided; exactly 50 percent want Bush to win and 50 percent want Gore. The truth—the genuine preference of the electorate—is split right down the middle. An ideal poll, one without any errors whatsoever, would show that the two candidates are exactly tied at 50 percent.

Let’s conduct a poll and see whether your answer corresponds to the truth. Now, it’s impractical to go back in time to 2000 and ask people their preferences. Luckily, there’s an excellent substitute for a 2000 voter: a coin. Heads, Bush; tails, Gore.

“Excuse me, sir . . . will you be voting for Bush or for Gore?” Flip the coin—it will come up for Bush 50 percent of the time and Gore 50 percent of the time, just like an exactly split electorate would.