A Field Guide to Lies: Critical Thinking in the Information Age by Daniel J. Levitin Read Free Book Online Page B

days,” you assume that I’m making a guess. If I say that “16.39 percent of new car sales are electric vehicles,” you assume that I know what I’m talking about. But you’d be confusing precision for accuracy. I may have made it up. I may have sampled only a small number of people near an electric-car dealership.
    Recall the Time magazine headline I mentioned earlier, which said that more people have cell phones than have toilets. This isn’t implausible, but it is a distortion because that’s not what the U.N. study found at all. The U.N. reported that more people had access to cell phones than to toilets, which is, as we know, a different thing. One cell phone might be shared among dozens of people. The lack of sanitation is still distressing, but the headline makes it sound like if you were to count, you’d find there are more cell phones in the world than there are toilets, and that is not supported by the data.
    Access is one of those words that should raise red flags when you encounter them in statistics. People having access to health care might simply mean they live near a medical facility, not that the facility would admit them or that they could pay for it. As you learned above,C-SPAN is available in 100 million homes, but that doesn’t mean that 100 million people are watching it. I could claim that 90 percent of the world’s population has “access” to A Field Guide to Lies by showing that90 percent of the population is within twenty-five miles of an Internet connection, rail line, road, landing strip, port, or dogsled route.
    Comparing Apples and Oranges
    One way to lie with statistics is to compare things—datasets, populations, types of products—that are different from one another, andpretend that they’re not. As the old idiom says, you can’t compare apples with oranges.
    Using dubious methods, you could claim that it is safer to be in the military during an active conflict (such as the present war in Afghanistan) than to be stateside in the comfort of your own home. Start with the3,482 active-duty U.S. military personnel who died in 2010. Out of atotal of 1,431,000 people in the military, this gives a rate of 2.4 deaths per 1,000. Across the United States, thedeath rate in 2010 was 8.2 deaths per 1,000. In other words, it is more than three times safer to be in the military, in a war zone, than to live in the United States.
    What’s going on here? The two samples are not similar, and so shouldn’t be compared directly. Active military personnel tend to be young and in good health; they are served a nutritious diet and have good health care. Thegeneral population of the United States includes the elderly, people who are sick, gang members, crackheads, motorcycle daredevils, players of mumblety-peg, and many people who have neither a nutritious diet nor good health care; their mortality rate would be high wherever they are. And active military personnel are not all stationed in a war zone—some are stationed in very safe bases in the United States, are sitting behind desks in the Pentagon, or are stationed in recruiting stations in suburban strip malls.
    U.S. News & World Report published an article comparing the proportion of Democrats and Republicans in the country going back to the 1930s. The problem is that sampling methods have changed over the years. In the 1930s and ’40s, sampling was typically done by in-person interviews and mail lists generated by telephone directories; by the 1970s sampling was predominantly just by telephone. Sampling in the early part of the twentieth century skewed toward those who tended to have landlines: wealthier people, who, at least at that time,tended to vote Republican. By the 2000s, cell phones were being sampled, which skewed toward the young, who tended to vote Democratic. We can’t really know if the proportion of Democrats to Republicans has changed since the 1930s because the samples are incompatible. We think we’re studying one thing