Skip to main content

Latest Post:

Updated example of using baby names to illustrate bimodal distributions.

The thing about my way of teaching stats is that my cool, novel examples get old really fast. Like, pop culture is on a thirty-day cycle. Anyway, YEARS ago, 2014 to be exact, I blogged about illustrating bimodal data distributions  using baby name data from the Social Security Administration. Specifically, when an older name comes back into vogue, it has a bimodal distribution when you plot time on the X axis.  I stand by this example. However, all of the data illustrations come from 2014. When our traditionally aged college students were 6 or 7. Which makes this example feel a little stale. However, here is some data,  courtesy of Redditor  fevaah ,  showing  old names that are back in vogue through 2025 ! And Eleanor, Violet, Nora, and Hazel are here, illustrating bimodal distributions for a new generation. If you used my old baby-name data, this is a quick, easy refresh for your lectures (or a fun new addition if you didn't).  If this idea was help...

John Bohannon's "I fooled millions into thinking chocolate helps weight loss. Here's how."

http://io9.com/i-fooled-millions-into-thinking-chocolate-helps-weight-1707251800
This story demonstrates how easy it is to do crap science, get it published in a pay-to-play journal, and market your research (to a global audience). Within this story, there are some good examples of Type I error, p-hacking, sensationalist science reporting, and, frankly, our obsession with weight and fitness and easy fixes—also, chocolate.


Here is the original story, as told to io9.com by the perpetrator of this very conscientious fraud, John Bohannon. Bohannon ran this con to expose just how open to corruption and manipulation the whole research publication process can be (BioMed Central scandal, for another example), especially when it just the kind of research that is bound to get a lot of media attention (LaCour scandal, for another example).

Bohannon set out to "demonstrate" that dark chocolate can contribute to weight loss. He ran an actual study (n = 26). He went on a fishing expedition and measured 18 different markers of health. He did find a significant relationship between chocolate and lower cholesterol (a good example of likely Type I error).

So a manuscript was created. Bohannon describes how quickly their manuscript was accepted at several pay to play journals (no peer review, either, opening up a class discussion about both peer review as well as the gradient of pay to play journals, some of which are peer-reviewed, many of which are not).

Dr. Bonahon then describes how he created a website called "The Institute of Diet and Health" to legitimize his research (to be clear, this Institute does not exist) as well as a press release for his study. Then, the media did his work for him. Once one outlet picked up his story, so did hundreds of others. One glimmer of hope: While the media just ran with this story, Bohannon states that internet discussion boards associated with the different media outlets actually yielded intelligent discussions that picked apart the flaws of the study.

So, I think that the whole io9.com piece would be a good reading assignment for a statistics or research methods class. Additionally, if you are looking to use this story in class, here is an NPR interview with Bohannon.

Popular posts from this blog

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing,  I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.
Read more

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr.  Molly Metz maintains a curated list of hilarious "How you doing?" scales.  2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables.  So, I decided to create a post about three ways to use these scales in your stats classes:  1) Teaching the basics of variables. 2) Nominal vs. ordinal scales.  3) Daily check-in with your students.  1. Teach your students the basics...
Read more

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:
Read more