The Canon by Natalie Angier Read Free Book Online Page B

unmistakably, starts to harden. By our late twenties or early thirties, the mind is made up: it has taken a stand on life, it knows from whence it speaks, and that commitment is reflected in its structure. Of course we can learn new things, up until the day we learn how to die; but chances are excellent that most adult learning takes place through the prism of preexisting skills. So if math is all Greek to you, take comfort in the following: (a) Why shouldn't it be? Many of the symbols used in math are letters from the Greek alphabet; and (b) it's Greek to a surprising number of scientists, too. As it happens, many biologists, chemists, geologists, and astronomers are relatively poor mathematicians. Bonnie Bassler of Princeton, considered one of the brightest young stars in the field of bacterial ecology, confessed to me that she is "terrible at math" and always has been. "I can balance my checkbook if I have a calculator," she said. "I can do fractions. But that's it. Somehow it didn't matter, and I ended up here."
    Even physicists, for whom math is indispensable, have their limits. Steven Weinberg may have won a Nobel Prize for helping to develop the mathematics that merged two of nature's four fundamental forces, electromagnetism and the weak force, into a single theoretical bundle
called the electroweak force—and this is not something you could do by reviewing your old high school algebra notes—yet he said he recently switched from particle physics to cosmology because the math in particle physics was getting beyond him.
    Yet while a mastery of math is not essential to appreciating and even practicing science, you can't avoid, while milling through the fairground of Science Mind, bumping into a few cousins from math's extended family. One is quantitative thinking, to which the next chapter is devoted: becoming comfortable with concepts of probability and randomness, and learning a few tricks about how to break a problem into tractable pieces and to whip up a back-of-a-wet-cocktail-napkin estimate of some seemingly incalculable figure, like, how many school buses are in your county, or how many people would have to hold hands to form a human chain around the globe and how many of them will be bobbing in open ocean and had better bring a life jacket, shark repellent, and a copy of their dental records just in case? True, you can likely find the answers to these and other fun FAQs on the Internet, yet the habit of thinking in stepwise, quantitative fashion, and facing a problem head-on rather than running off screaming to Google, is worth cultivating. Second only to their desire that science be seen as a dynamic and creative enterprise rather than a calcified set of facts and laws, scientists wish that people would learn enough about statistics—odds, averages, sample sizes, and data sets—to scoff with authority at crooked ones. Through sound quantitative reasoning, they reason, people might resist the lure of the anecdote and the personal testimonial, the deceptive N, or sample size, of "me, my friends, the doorman, and the barista at Caribou." With a better appreciation for the qualities of quantities, people might be able to set aside, if only temporarily, the stubbornness of a human brain that evolved to focus on the quirks and peccadilloes of a small, homogeneous tribe, rather than on the daunting population densities and polycultural vortices that characterize life in contemporary Gotham City. There is a little principle called the law of large numbers, which among other things means that if the group you're considering is very big, nearly anything is possible. Events that would be rare on a limited scale become not merely common, but expected. One favorite example among the numerati is that of repeat lottery winners, people who have won big prizes two or more times and who invariably provoke clucks of awe, envy, what-are-the-odds. "The really amazing thing would be if nobody won twice," said