A Field Guide to Lies: Critical Thinking in the Information Age Read Online Free PDF Page B

sinister example: an implied double y-axis graph with no axes on either side!
    Drawn properly, the graph would look like this:

    Here, we see that abortions increased modestly, compared to the reduction in cancer services.
    There is another thing suspicious about the original graph: Such smooth lines are rarely found in data. It seems more likely that the graph maker simply took numbers for two particular years, 2006 and 2013, and compared them, drawing a smooth connecting line between them. Perhaps these particular years were chosen intentionally to emphasize differences. Perhaps there were great fluctuations in the intervening years of 2007–2012; we don’t know. The smooth lines give the impression of a perfectly linear (straight line) function, which is very unlikely.
    Graphs such as this do not always tell the story that people think they do. Is there something that could account for these data, apart from a narrative that Planned Parenthood is on a mission to perform as many abortions as it can (and to let people die of cancer at the same time)? Look at the second graph. In 2006, Planned Parenthood performed 2,007,371 cancer services, and 289,750 abortions, nearly seven times as many cancer services as abortions. By 2013, this gap had narrowed, but the number of cancer services was still nearly three times the number of abortions.
    Cecile Richards, the president of Planned Parenthood, had an explanation for this narrowing gap. Changing medical guidelines for some anti-cancer services, like Pap smears, reduced the number of people for whom screening was recommended. Other changes, such as social attitudes about abortion, changing ages of the population, and increased access to health care alternatives, all influence these numbers, and so the data presented do not prove that Planned Parenthood has a pro-abortion agenda. It might—these data are just not the proof.

H IJINKS WITH H OW N UMBERS A RE R EPORTED
    You’re trying to decide whether to buy stock in a new soft drink and you come across this graph of the company’s sales figures in their annual report:

    This looks promising—Peachy Cola is steadily increasing its sales. So far, so good. But a little bit of world knowledge can be applied here to good effect. The soft-drink market is very competitive. Peachy Cola’s sales are increasing, but maybe not as quickly as acompetitor’s. As a potential investor, what you really want to see is how Peachy’s sales compare to those of other companies, or to see their sales as a function of market share—Peachy’s sales could go up only slightly while the market is growing enormously, and competitors are benefiting more than Peachy is. And, as this example of a useful double y-axis graph demonstrates, this may not bode well for their future:

    Although unscrupulous graph makers can monkey with the scaling of the right-hand axis to make the graph appear to show anything they want, this kind of double-y-axis graph isn’t scandalous because the two y-axes are representing different things, quantities that couldn’t share an axis. This was not the case with the Planned Parenthood graph here , which was reporting the same quantity on the two different axes, the number of performed procedures. That graph was distorted by ensuring that the two axes, although they measure the same thing, were scaled differently in order to manipulate perception.
    It would also be useful to see Peachy’s profits: Through manufacturing and distribution efficiencies, it may well be that they’re making more money on a lower sales volume. Just because someone quotes you a statistic or shows you a graph, it doesn’t mean it’s relevant to the point they’re trying to make. It’s the job of all of us to make sure we get the information that matters, and to ignore the information that doesn’t.
    Let’s say that you work in the public-affairs office for a company that manufactures some kind of device—frabezoids. For the last several