Tag Archives: innumeracy

Sorting the good from the bad statistics about Evangelicals

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Sociologist Bradley Wright talks with Christianity Today about his latest book: Christians Are Hate-Filled Hypocrites…and Other Lies You’ve Been Told: A Sociologist Shatters Myths From the Secular and Christian Media. Here is CT’s quick summary of the argument:

Young people are not abandoning church. Evangelical beliefs and practices get stronger with more education. Prayer, Bible reading, and evangelism are up. Perceptions about evangelicals have improved dramatically. The data are clear on these matters, says University of Connecticut sociologist Bradley Wright, but evangelicals still want to believe the worst statistics about themselves.

One question to then ask is why Evangelicals buy into these negative statistics. The subculture argument, when applied to evangelicals, might suggest that these numbers help keep people fired up by reminding them that the group could lose its distinctiveness if drastic action is not taken.

Wright suggests his goal is to encourage Evangelicals:

This is not a call for complacency but for encouragement. Why not say, “We’re reading our Scriptures more than most other religious traditions; let’s do even better”? Instead, what we hear is, “Christianity’s going to fail. You’re all a bunch of failures. But if you buy my book, listen to my sermon, or go to my conference, I’ll solve everything.” These fear messages demoralize people, hinder the message of the church, and hide real problems.

I would like to see exactly what statistics he looks at and debunks. Wright is not the first to suggest Evangelicals have some issues with statistics.

Fighting innumeracy and “proofiness”

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A new book by journalist Charles Seife examines how figures and statistics are poorly used in public debates. I like his idea of “proofiness” which seems similar to the concept of “truthiness.” Here are some of the types of bad statistics he points out:

Falsifying numbers is the crudest form of proofiness. Seife lays out a rogues’ gallery of more subtle deceptions. “Potemkin numbers” are phony statistics based on erroneous or nonexistent calculations. Justice Antonin Scalia’s assertion that only 0.027 percent of convicted felons are wrongly imprisoned was a Potemkin number derived from a prosecutor’s back-of-the-envelope estimate; more careful studies suggest the rate might be between 3 and 5 percent.

“Disestimation” involves ascribing too much meaning to a measurement, relative to the uncertainties and errors inherent in it. In the most provocative and detailed part of the book, Seife analyzes the recounting process in the astonishingly close 2008 Minnesota Senate race between Norm Coleman and Al Franken. The winner, he claims, should have been decided by a coin flip; anything else is disestimation, considering that the observed errors in counting the votes were always much larger than the number of votes (roughly 200 to 300) separating the two candidates.

“Comparing apples and oranges” is another perennial favorite. The conservative Blue Dog Democrats indulged in it when they accused the Bush administration of borrowing more money from foreign governments in four years than had all the previous administrations in our nation’s history, combined. True enough, but only if one conveniently forgets to correct for inflation.

Books like these are needed in our society as politicians often debate through numbers. Without a proper understanding of who is using these numbers, where they come from, and what they mean, the public will have difficulty understanding what is going on. (And this may be the aim of politicians.)

(Based on this review, his arguments and concepts seem similar to those of sociologist Joel Best.)

Quick Review: Stat-Spotting

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Sociologist Joel Best has recently done well for himself by publishing several books about the misuse of statistics. This is an important topic: many people are not used to thinking statistically and have difficulty correctly interpreting statistics even though they are commonly used in media stories. Best’s most recent book on this subject, published in 2008, is Stat-Spotting: A Field Guide to Identifying Dubious Data. A few thoughts on this text:

1. One of Best’s strong points is that his recommendations are often based in common-sense. If a figure strikes you as strange, it probably is. He has tips about keeping common statistical figures in your mind to help keep sense of certain statistics. Overall, he suggests a healthy skepticism towards statistics: think about how the statistic was developed and who is saying it.

2. When the subtitle of the book says “field guide,” it means a shorter text that is to the point. Best quickly moves through different problems with statistical data. If you are looking for more thorough explanations, you should read Best’s 2001 book Damned Lies and Statistics. (A cynical reader might suggest this book was simply a way to make more money of topics Best has already explored elsewhere.)

3. I think this text is most useful for finding brief examples of how to analyze and interpret data. There are numerous examples in here that could start off a statistics lesson or could further illustrate a point. The examples cover a variety of topics and sources.

This is a quick read that could be very useful as a simple guide to combating innumeracy.