Tag Archives: statistics

Introduction to Freakonomics

“This book, then, has been written from a very specific worldview, based on a few fundamental ideas:

Incentives are the cornerstone of modern life...

The conventional wisdom is often wrong…

Dramatic effects often have distant, even subtle, causes…

“‘Experts’–from criminologists to real-estate agents–use their information advantage to serve their own agenda…

Knowing what to measure and how to measure it makes a complicated world much less so….” (p. 13-14)

Alternative Medicine and Statistical Validation

“The resistance to statistical evidence is even more pronounced with regard to ‘alternative medicine,’ a vast field that encompasses everything from herbal supplements to energy therapy to yoga…Many adherents and advocates of alternative medicine reject not only Western treatments but the Westernized notion of statistical testing. They sometimes claim that their practices are too ‘individual’ or ‘holistic’ to study scientifically and instead rely on anecdotes and case studies without adequate controls or control groups for comparison. I’m agnostic about whether alternative medicine is effective. But it verges on idiocy to claim that the effectiveness cannot be tested. If it really is important, as alternative medicine advocates claim, to take into account a larger set of information about the patient…then providers who do so should produce better results…When it comes to the back-end inquiry of finding out which treatments are effective, there is no East and West. I throw my lot with two past editors-in-chief of the New England Journal of Medicine, Marcia Angell and Jerome Kassirer: ‘It is time for the scientific community to stop giving alternative medicine a free ride. There cannot be two kinds of medicine–conventional and alternative. There is only one medicine that has been adequately tested and medicine that has not, medicine that works and medicine that may or may not work.” (p. 229)

Statistics Go Beyond the Numbers

“One can crunch numbers and still have a passionate and caring soul. You can still be creative. You just have to be willing to put your creativity and your passions to the test to see if they really work.” (p. 215)

Using Statistics to Predict a Baby’s Due Date Beats Traditional Method

“Most doctors don’t even give the most accurate prediction of the due date. They still often calculate the due date based on the quasi-mystical formula of Franz Naegele, who believed in 1812 that ‘pregnancy lasted ten lunar months from the last menstrual period.’ It wasn’t until the 1980s that Robert Mittendorf and his coauthors crunched numbers on thousands of births to let the numbers produce a formula for the twentieth century. Turns out that pregnancy for the average woman is eight days longer than the Naegele rule, but it’s possible to make even more refined predictions. First-time mothers deliver about five days later than mothers who have already given birth. Whites tend to deliver later than nonwhites. The age of the mother, her weight, and her nutrition all help predict her due date. Physicians using the crude Naegele rule cruelly set up first-time mothers for disappointment.” (p. 209)

Statistical Thinking Versus Intuition

“The rise of statistical thinking does not mean the end of intuition or expertise…Increasingly, decision makers will switch back and forth between their intuitions and data-based decision making. Their intuitions will guide them to ask new questions of the data that non-intuitive number crunchers would miss. And databases will increasingly allow decision makers to test their intuitions–not just once, but on an ongoing basis.” (pp. 195-196)

Getting People to Accept Statistical / Data Mining Approaches

“There’s almost an iron-clad law that it’s easier for people to warm up to applications of Super Crunching outside of their own area of expertise. It’s devilishly hard for traditional, non-empirical evaluators to even consider the possibility that quantified predictions might do a better job than they can on their own home turf. I don’t think this is primarily because of blatant self-interest in trying to keep our jobs. We humans just overestimate our ability to make good decisions and we’re skeptical that a formula that necessarily ignores innumerable pieces of information could do a better job than we could.” (p. 150)

Research Says Physical Exams Are Unnecessary, Yet Physicians Persist in Doing Them

“Even when statistical studies exist, doctors are often blissfully unaware of–or, worse yet, deliberately ignore–statistically prescribed treatments just because that’s not the way they were taught to treat. Dozens of studies dating back to 1989 found little support for many of the tests commonly included in a typical annual physical for symptom-less people. Routine pelvic, rectal, and testicular exams for those with no symptoms of illness haven’t made any difference in overall survival rates. The annual physical exam is largely obsolete. Yet physicians insist on doing them, and in very large numbers.”