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HARDBOUND

Spot The Flaw
Gary Smith breaks down how misled assumptions are born and statistics is manipulated

More than a century ago, Sherlock Holmes pleaded to his long-suffering friend Watson, “Data! Data! Data! I can’t make bricks without clay.” Today, Holmes’s wish has been granted in spades. Powerful computers sift through data, data, and more data. The problem is not that we don’t have enough data, but that we are misled by what we have in front of us. It is not entirely our fault. You can blame it on our ancestors.

The evolution of certain traits is relatively simple. Living things with inheritable traits that help them survive and reproduce are more likely to pass these traits on to future generations than are otherwise similar beings that do not have these traits. Continued generation after generation, these valuable inherited traits become dominant.

The well-known history of the peppered moth is a simple, straightforward example. These moths are generally light-colored and spend most of their days on trees where they are camouflaged from the birds that prey on them. The first dark-colored peppered moths were reported in England in 1848, and by 1895, 98 percent of the peppered moths in Manchester were dark-colored. In the 1950s, the pendulum started swinging back. Dark-colored moths are now so rare that they may soon be extinct.

The evolutionary explanation is that the rise of dark-colored moths coincided with the pollution caused by the Industrial Revolution. The blackening of trees from soot and smog gave dark-colored moths the advantage of being better camouflaged and less likely to be noticed by predators. Because dark-colored moths were more likely to survive long enough to reproduce, they came to dominate the gene pool. England’s clean-air laws reversed the situation, as light-colored moths are camouflaged better on pollution-free trees. Their survival advantage now allows them to flourish.

Other examples of natural selection are more subtle. For example, studies have consistently found that men and women are more attracted to people with symmetrical faces and bodies. This isn’t just cultural — it is true across different societies, true of babies, and even found in other animals. In one experiment, researchers clipped the tail feathers of some male barn swallows to make them asymmetrical. Other males kept their symmetrical tail feathers. When female swallows were let loose in this mating pool, they favored the males with symmetrical feathers. This preference for symmetry is not just a superficial behavior. Symmetry evidently indicates an absence of genetic defects that might hamper a potential mate’s strength, health, and fertility. Those who prefer symmetry eventually dominate the gene pool because those who don’t are less likely to have offspring that are strong, healthy, and fertile.

Believe it or not, evolution is also the reason why many people took Paul and Mani seriously. Our ingrained preference for symmetry is an example of how recognizing patterns helped our human ancestors survive and reproduce in an unforgiving world. Dark clouds often bring rain. A sound in the brush may be a predator. Hair quality is a sign of fertility. Those distant ancestors who recognized patterns that helped them find food and water, warned them of danger, and attracted them to fertile mates passed this aptitude on to future generations. Those who were less adept at recognizing patterns that would help them survive and reproduce had less chance of passing on their genes. Through countless generations of natural selection, we have become hardwired to look for patterns and to think of explanations for the patterns we find. Storm clouds bring rain. Predators make noise. Fertile adults have nice hair.

Unfortunately, the pattern-recognition skills that were valuable for our long-ago ancestors are ill-suited for our modern lives, where the data we encounter are complex and not easily interpreted. Our inherited desire to explain what we see fuels two kinds of cognitive errors. First, we are too easily seduced by patterns and by the theories that explain them. Second, we latch onto data that support our theories and discount contradicting evidence. We believe stories simply because they are consistent with the patterns we observe and, once we have a story, we are reluctant to let it go.

When you keep rolling sevens at the craps table, you believe you are on a hot streak because you want to keep winning. When you keep throwing snake eyes, you believe you are due for a win because you want to start winning. We don’t think hard enough about the fact that dice do not remember the past and do not care about the future. They are inanimate; the only meaning they carry is what we hopeful humans ascribe to them. If the hot streak continues or the cold streak ends, we are even more convinced that our fanciful theory is correct. If it doesn’t, we invent excuses so that we can cling to our nonsensical story.

We see the same behavior when athletes wear unwashed lucky socks, when investors buy hot stocks, or when people throw good money after bad, confident that things must take a turn for the better. We yearn to make an uncertain world more certain, to gain control over things that we do not control, to predict the unpredictable. If we did well wearing these socks, then it must be that these socks help us do well. If other people made money buying this stock, then we can make money buying this stock. If we have had bad luck, our luck has to change, right? Order is more comforting than chaos.

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