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Showing posts with the label causality

University of Pittsburgh's National Sports Brain Bank

 I have written about the NFL's response to concussion data as a case study of how to obfuscate data. This has been covered in many places, including in The Atlantic and on PBS . In my experience, concussions are a prime source of conversation for traditionally college-aged students. Many of them were high school athletes. Fewer are college athletes. Most college students have personally experienced a concussion or loves someone who has. Now, the University of Pittsburgh is opening the National Sports Brain Bank . This is for athletes, not just football players. Two former Steelers have promised their brains, as have two scientists who played contact sports.  Here is a press release from the University of Pittsburgh . Here is a news report  featuring the two Steelers who have promised to donate their brains. However, as described by Aschwander, we still don't know how many football players have CTE (please read this piece, it is such good stats literacy from Aschwander...

Damn you, auto-correct: Statistics edition

Legit funny, but also a gentle way to remind our students that Word will not flag a correctly spelled word that is not the word you want.

Logical Fallacy Ref Meme

So, I love me some good statsy memes. They make a brief, important point that sticks in the heads of students. I've recently learned of the Logical Fallacy Ref meme. Here are a couple that apply to stats class:

Aschwanden's "You Can’t Trust What You Read About Nutrition"

Fivethirtyeight provides lots of beautiful pictures of spurious correlations found by their own in-house study. At the heart of this article are the limitations of a major tool use in nutritional research, the Food Frequency Questionnaire (FFQ). The author does a mini-study, enlisting the help of several co-workers and fivethirtyeight.com readers. They track track their own food for a week and reflect on how difficult it is to properly estimate and recall food (perhaps a mini-experiment you could do with your own students?). And she shares the spurious correlations she found in her own mini-research: Aschwanden also discusses how much noise and lack of consensus their is in real, published nutritional research (a good argument for why we need replication!):  http://fivethirtyeight.com/features/you-cant-trust-what-you-read-about-nutrition/ How to use in class: -Short comings of survey research, especially survey research that relies on accurate memories -...

Richard Harris' "Why Are More Baby Boys Born Than Girls?"

51% of the babies born in the US are male. Why? For a long time, people just assumed that the skew started at conception. Then Steven Orzack decided to test this assumption. He (and colleagues) collected sex data from abortions, miscarriages, live births (30 million records!), fertility clinics (140,00 embryos!), and different fetal screening tests (90,000 medical records!) to really get at the root of the sex skew/conception assumption. And the assumption didn't hold up: The sex ratio is pretty close to 50:50 at conception. Further analysis of the data found that female fetuses are more likely to be lost during pregnancy. Original research article here . Richard Harris' (reporting for NPR) radio story and interview with Orzack here . Use this story in class as a discussion piece about long held (but never empirically supported) assumptions in the sciences and why we need to conduct research in order to test such assumptions. For example: 1) Discuss the weaknesses of previo...

Emily Oster's "Don't take your vitamins"

My favorite data is data that is both counter-intuitive and tests the efficacy of commonly held beliefs. Emily Oster's (writing for 538) presents such  data in her investigation of vitamin efficacy . The short version of this article: Data that associates vitamins with health gains are based on crap observational research. More recent and better research throws lots of shade on vitamin usage. Specific highlights that could make for good class discussion: -This article explains the flaws in observational research as well as an example of how to do good observational research well (via The Physician's Health Study , with large samples of demographically similar individuals as described in the portion of the article featuring the Vitamin E study). This point provides an example of why controlled, double-blind lab research is the king of all the research. -This is an accessible example as most of your students took their Flintstones. -The article also demonstrates The Thir...