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

go-getters. They might have earned as high a salary if they had attended a college with a lesser reputation, or even no college at all. (Mark Zuckerberg, Matt Damon, and Bill Gates are financially successful people who dropped out of Harvard.)
    If you simply can’t reach some segment of the population, such as military personnel stationed overseas, or the homeless and institutionalized, this sampling bias is called coverage error becausesome members of the population from which you want to sample cannot be reached and therefore have no chance of being selected.
    If you’retrying to figure out what proportion of jelly beans in a jar are red, orange, and blue, you may not be able to get to the bottom of the jar. Biopsies of organs are often limited to where the surgeon can collect material, and this is not necessarily a representative sample of the organ. In psychological studies, experimental subjects are often college undergraduates, who are not representative of the general population. There is a great diversity of people in this country, with differing attitudes, opinions, politics, experiences, and lifestyles. Although it would be a mistake to say that all college students are similar, it would be equally mistaken to say that they represent the rest of the population accurately.
    Reporting Bias
    People sometimes lie when asked their opinions. A Harvard graduate may overstate her income in order to appear more successful than she is, or may report what she thinks she should have made if it weren’t for extenuating circumstances. Of course, she may understate as well so that the Harvard Alumni Association won’t hit her up for a big donation. These biases may or may not cancel each other out. The average we end up with in a survey of Harvard graduates’ salaries is only the average of what they reported, not what they actually earn. The wealthy may not have a very good idea of their annual income because it is not all salary—it includes a great many other things that vary from year to year, such as income from investments, dividends, bonuses, royalties, etc.
    Maybe you ask people if they’ve cheated on an exam or on theirtaxes. They may not believe that your survey is truly confidential and so may not want to report their behavior truthfully. (This is a problem with estimating how many illegal immigrants in the U.S. require health care or are crime victims; many are afraid to go to hospitals and police stations for fear of being reported to immigration authorities.)
    Suppose you want to knowwhat magazines people read. You could ask them. But they might want to make a good impression on you. Or they might want to think of themselves as more refined in their tastes than they actually are. You may find that a great many more people report reading the New Yorker or the Atlantic than sales indicate, and a great many fewer people report reading Us Weekly and the National Enquirer. People don’t always tell the truth in surveys. So here, you’re not actually measuring what they read, you’re measuring snobbery.
    So you come up with a plan: You’ll go to people’s houses and see what magazines they actually have in their living rooms. But this too is biased: It doesn’t tell you what they actually read, it only tells you what they choose to keep after they’ve read it, or choose to display for impression management. Knowing what magazines people read is harder to measure than knowing what magazines people buy  (or display). But it’s an important distinction, especially for advertisers.
    What factors underlie whether an individual identifies as multiracial? If they were raised in a single racial community, they may be less inclined to think of themselves as mixed race. If they experienced discrimination, they may be more inclined. We might define multiraciality precisely, but it doesn’t mean that people will report it the way we want them to.
    Lack of Standardization
    Measurements must be standardized. There must