I maintain that relative versus absolute risk is a concept that we absolutely must teach in intro stats. I have given some examples of this before ( murder ! COVID !) but here is another one that hits home for my fellow Great Lakers. In particular, this one is for my friends in Detroit, Toledo, Cleveland, and Buffalo  Up here in Erie, a common point of discussion is how frozen Lake Erie is. Because once it freezes, the lake's moisture no longer feeds Dread Lake Effect Snow.   I like this example because you can easily perform the math in front of your class, demonstrating that 26.14% is 103.45% of 12.85%. At the same time, you have the visual to demonstrate that the vast majority of the lake was still unfrozen even with a 103.45% increase. 

When I teach the basics of probability in Intro Stats, I always emphasize absolute vs. risk. I am delighted to have a brand new example. Thanks to Sy Islam for sending it my way. Here is the headline  from The New York Post: So, one murder is too many murders. A 60% increase feels very scary. Because relative risk is always the scary risk.  Since this reporting is about something that is very serious, the reporting itself should be serious, right? Well, what were the absolute values for subway murders? I mean, The New York Post would never, ever want to instill fear in people, right? Well, despite this headline, The New York Post, much to its credit, did include the absolute data in the actual article: Eight murders, versus five in the previous years. Which is too terrible, but not nearly as frightening as a (checks notes) SOARING 60% increase. Anyway. Ta-da! Use this in your class. 

 https://www.npr.org/sections/goatsandsoda/2023/05/10/1175303067/a-plastic-sheet-with-a-pouch-could-be-a-game-changer-for-maternal-mortality https://www.bmj.com/content/381/bmj.p1055 I love this study, in and of itself, because it is based on research that will save women's lives without spending a lot of money. I love it.  Here is a link to the original study . I learned about it from an NPR story about the research by Rhitu Chaterjee . I also love it because it is an accessible example of a bunch of statistics things: Dependent variables...operationalizing variables...why cross-cultural research and solutions aren't just lip service to diversity...how control groups in medical research are very different than control groups in psychology research...absolute vs. relative risk. -Dependent variables/operationalized variables: This study clearly illustrates the power of measurement and operationalization. The researchers wanted to create a way to better assess post-childbirth h...

Do you know what bugs me? How much time different intro stats textbooks spend talking about probability, lots of A not B stuff*, lots of probability associated with the normal distribution, etc. But we don't take advantage of the discussion to warn their students about the evils of relative vs. absolute risk. #statsliteracy Relative risk is the most clickbaity abuse of statistics that there is. Well, maybe the causal claims based on correlational data are more common. But I think the relative risk is used to straight-up scare people, possibly changing their behaviors and choices. I thought of it most recently when The Daily Mail (bless) used explained the difference in COVID-19 risk between dog owners and non-dog owners .   Here is the data described in the headline, straight from the original paper : Really, Daily Mail? How dare you. I think the most clever, trickiest, sneakiest ways to mislead with data are by not lying with data at all. Most truncated y-axes display actual ...

Kyne is a drag queen, a contender on Canada's Drag Race (which will air in July of this year). She also posts lots of photos displaying her exceptional make-up and costuming skills. Source:  https://www.instagram.com/p/CAlWzU1AN0d/ She also LOVES statistics and math. Better yet, she has a talent for concise and straight-forward explanations of math and statistical topics. Perfect for teaching stats. Kyne posts most of her math content directly to TikTok , but also maintains a channel for her math content on Instagram . Below, I've compiled some of her stats content:  Misleading graphs, and also very important, thinking your way through misleading graphs (CNBC graph that exaggerated job growth in the US).  Several posts ( 1 , 2 , 3 ) break down and describing the flawed reasoning present in several viral posts about crime rates, data, and race. I think these posts are especially helpful for novice statisticians and she walks the viewer through the logic of the data.  ...

http://gazomg.deviantart.com/art/Star-Trek-Redshirt-6-The-Walking-Dead-483111105 io9 recaps a talk given by mathematician  James Grime . He addressed the long running Star Trek joke that the first people to die are the Red Shirts. Using resources that detail the ins and outs of Star Trek, he determined that: This makes for a good example of absolute vs. relative risk. Sure, more red shirts may die, absolutely, but proportionally? They only make up 10% of the deaths. Also, I think this is a funny example of using archival data in order to understand an actual on-going Star Trek joke. For more math/Star Trek links, go to space.com's treatment of the speech.

Refutation to Anti-vaccination Memes  came up with this excellent illustration to explain why anti-vaxxers shouldn't claim a "win" just because more vaccinated people than unvaccinated people get sick during an outbreak. This example has a bit more credence if paired with actual immunization rate/infection rate data. For instance, in a case when an outbreak has occurred, and most infected are immunized, but there were still some un-immunized individuals. To further this case, yes, most people in America are immunized . However, here  is an example of an outbreak that has been linked to un-vaccinated folks. How to use it in class: -Base rate fallacy (which DOES matter when making an argument with descriptive stats!) -Relative v. absolute risk. -Making sense of and contextualizing descriptive statistics.

Two scientists, Lazris and Rifkin, want to better illustrate the risks and benefits associated with preventative medicine. They do so by asking people to imagine theaters filled with 1,000 people, and describing the costs and benefits for different preventative procedures by discussing how many people in the theater will be saved or perish based on current efficacy data. One such video can be viewed here and illustrates the absolute and relative risks associated with mammography. They are attempting to demystify statistics and better explain the risks and benefits by showing an animated theater filled with 1,000 women, and showing how many women actually have their lives saved by mammograms (see screen shot below)... ...as well as the number of women who received false positives over the course of a life time... A screen shot of the video, which is trying a new way to illustrate risk. ...the video also illustrates how a "20% reduction in breast cancer deaths" ca...

This study, which found a link between maternal Tylenol usage during pregnancy and ADHD, has been making the rounds, particularly in the Academic Mama circles I move in. Being pregnant is hard. For just about every malady, the only solution is to stay hydrated. With a compromised bladder. But at least pregnant women have Tylenol for sore hips and bad backs. For a long time, this has been the only safe OTC pain reliever available to pregnant women. But a recent research article has cast doubt on this advice. A quick read of this article makes it sound like you are cursing your child with a lifetime of ADHD if you take Tylenol. A nd this article has become click-bait fodder. But these findings have some pretty big caveats.  Harris published this reaction piece at NPR . It is a good teaching example of media hype vs. incremental scientific progress and the third (or fourth or fifth) variable problem. It also touches on absolute vs. relative risk. NOTE: There are well-documente...

Gerd "I love heuristics" Gigernezer talking about the misinterpretation of research by the medi a (in particular, misinterpretation of data about oral contraceptives leads to increases in abortions). He argues that such misinterpretation isn't just bad reporting, but unethical.