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Thursday, September 09, 2021

Review: The Data Detective

 The Data Detective is Tim Harford's response to "How to Lie with Statistics". What surprised me the most about the book was the information in the first chapters, where Harford reveals that the latter book was written for the purposes of obfuscating the link between cancer and tobacco use. In other words, it was designed to make the public distrust statistics in favor of smoking.

Harford's response in the book is that truth is far more interesting than lying, and the principles behind discovering the truth are universal (and to be honest, not different from the scientific method) and do a better job of protecting you from misinformation than blithe rules. In some sense, the book didn't meet my expectations, because I expected some sort of overview or explanation of statistics, but all I got instead was a series of rules about lying to yourself and how to prevent that.

However, I quickly forgave Harford that. The stories in the books are just too good:

I had a little chuckle about the Tom Peters and Robert Waterman book In Search of Excellence, a blockbusting business bestseller published in 1982, which offered management lessons gleaned from studying forty-three of the most outstanding corporations of that time. If they really were paragons of brilliant management, then one might have expected their success to last. If instead they were the winners of an invisible lottery, the beneficiaries of largely random strokes of good fortune, then we would expect that the good luck would often fail to last. Sure enough, within two years almost a third of them were in serious financial trouble. It’s easy to mock Peters and Waterman—and people did—but the truth is that a healthy economy has a lot of churn in it. Corporate stars rise, and burn out. Sometimes they have lasting qualities, sometimes fleeting ones, and sometimes no qualities at all, bar some luck. By all means look at the success stories and try to learn lessons, but be careful. It is easy, in Nassim Taleb’s memorable phrase, to be “fooled by randomness.” (kindle loc 1858)

 Over the course of eighteen years, the nineteenth-century German doctor Carl Wunderlich assembled over a million measurements of body temperature, gathered from more than 25,000 patients. A million measurements! It’s a truly staggering achievement given the pen-and-paper technology of the day. Wunderlich is the man behind the conventional wisdom that normal body temperature is 98.6°F. Nobody wanted to gainsay his findings, partly because the dataset was large enough to command respect, and partly because the prospect of challenging it with a bigger, better dataset was intimidating. As Dr. Philip Mackowiak, an expert on Wunderlich, put it, “Nobody was in a position or had the desire to amass a dataset that large.”12 Yet Wunderlich’s numbers were off; we’re normally a little cooler (by about half a Fahrenheit degree).13 So formidable were his data that it took more than a hundred years to establish that the good doctor had been in error.* (kindle loc 2507)

Hardford's rules include making sure that the data collected is not subject to selection bias, that it defines its terms correctly, that it's not subject to p-hacking (yes, there's a section on the reproducibility crisis), and that the  data is inspectable and subject to audits, open-source style.

The closing of the chapter provides hope that the way to defeat misinformation is by engaging people's curiosity:

After a long and fruitless search for an antidote to tribalism, Kahan could be forgiven for becoming jaded.5 Yet a few years ago, to his surprise, he and his colleagues stumbled upon a trait that some people have—and that other people can be encouraged to develop—that inoculates us against this toxic polarization. On the most politically polluted, tribal questions, where intelligence and education fail, this trait does not. And if you’re desperately, burningly curious to know what it is—congratulations. You may be inoculated already. Curiosity breaks the relentless pattern. Specifically, Kahan identified “scientific curiosity.” That’s different from scientific literacy. The two qualities are correlated, of course, but there are curious people who know rather little about science (yet), and highly trained people with little appetite to learn more...The scientifically curious people Kahan’s team studied were originally identified with simple questions, buried in a marketing survey so that people weren’t conscious that their curiosity was being measured. One question, for example, was “How often do you read science books?” Scientifically curious people are more interested in watching a documentary about space travel or penguins than a basketball game or a celebrity gossip show. And they didn’t just answer survey questions differently, they also made different choices in the psychology lab. In one experiment, participants were shown a range of headlines about climate change and invited to pick the “most interesting” article to read...Scientifically curious people—Republicans or Democrats—were different. They were happy to grab an article that ran counter to their preconceptions, as long as it seemed surprising and fresh. And once you’re actually reading the article, there’s always a chance that it might teach you something. (Kindle Loc 4009-4037)

And of course, that's what luminaries like Carl Sagan have been doing all along. They were smarter than everyone gave them credit for. Needless to say, I highly recommend this book, and am going on to read more Harford.

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