Flowingdata is great. They create lots of exciting data visualizations and share other people's visualizations.  This visualization from Flowingdata is especially significant.   I think it illustrates base rate fallacies beautifully. Moreover, it is applied to a very crucial issue: Immunizations. The base rate fallacy has been used repeatedly to attack the efficacy of vaccines . In particular, instances when vaccinated people catch diseases for which they have been vaccinated. Frequently, such arguments fail to consider base rate data regarding how many more people are vaccinated.  This illustration from Marc Rummy is elegant and straightforward and explains a mathy/sampling/statsy concept without any actual math. I love it.  Also, this illustration has been updated recently with a bit more text to explain everything: Apparently this picture I made that was part of a post 4 months ago recently went viral. Here's a new & improved version that includes the explana...

 I found this Tweet, which leads to a brief report on BBC. A recent report from the World Obesity Federation shows COVID death rates are higher in countries where more than half the population is overweight. Cause and effect, or bad statistics? @TimHarford and @d_spiegel explore - with some maths from me. You can listen on @BBCSounds https://t.co/hevepmz8RC — stuart mcdonald (@ActuaryByDay) March 14, 2021 The BBC has a show called "More or Less," and they explained a recent research finding connecting obesity to COVID 19 deaths.  Here is the original research study . Here is a pop treatment of the original study . For more stats news, you can follow  "More or Less" on Twitter . And they cram, like, a half dozen lessons in this story. It is amazing. I've tried to highlight some of the topics touched upon in this story. How can you use it in class? I think it would be a good final exam question. You could have your students listen to the story, and highlight ...

In just over five minutes, this concise, clear TEDed talk that explains a) false positives, b) base rate fallacy, and c) conditional probability. And it manages to explain each of those three concepts individual while also showing how those three concepts interact. That's a lot of bang for your buck. **Note: This video is sort of a commercial for Brilliant.org, which claims to teach critical thinking via riddles and questions. FYI.

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.