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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...
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Smart's "The differences in how CNN MSNBC & FOX cover the news"

https://pudding.cool/2018/01/chyrons/ This example doesn't demonstrate a specific statistical test. Instead, it demonstrate how data can be used to answer a hotly contested question: Are certain media outlets biased? How can we answer this? Charlie Smart, working for The Pudding, addressed this question via content analysis. Here is how he did it: And here are some of their findings: Yes, Fox News was talking about the Clintons a lot. While over at MSNBC, they discussed the investigation into Russia and the 2016 elections ore frequently. While kneeling during the anthem was featured on all networks, it was featured most frequently on Fox And context matters. What words are associated with "dossier"? How do the different networks contextualize President Trump's tweets? Another reason I like this example: It points out the trends for the three big networks. So, we aren't a bunch of Marxist professors ragging on FOX, and we ar...
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Moderation, esophageal cancer, and really hot tea.

You know what, I've been doing this blog for YEARS and I don't have a single example of moderation. Until now. This CNN story summarizes brand new research findings that indicate that alcohol and/or tobacco use mediate the relationship between drinking really hot tea and developing esophageal cancer. So, the really hot tea-cancer relationship does not exist in the absence of smoking and/or alcohol consumption, but it is there if you do indulge in either smoking or alcohol consumption. And writing this post reminded me of this Arrested Development moment: Aside: -This article could also be a good example of the need for cross cultural research: Americans don't love tea as much as other parts of the world do. And, super hot tea (145 degrees +) is very popular outside of the US and Europe. The present research was conducted in China.
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We Rate Dogs, Psychometrics, and Operationalization.

This is a very silly example for psychometrics. It highlights how hard it is to quantify certain things, but we keep on trying. While psychologists struggle with creating scales to rate things like intelligence, aggression, and anxiety, WeRateDogs struggles with encompassing all that is good about dogs on a 1-10 rating scale. See below. WeRateDogs is a Twitter account. And they rate dogs. And every single dogs is rated between 12 and 15 out of 10 points, because every dog is a very good dog. But...I do see the psychometric flaw of their rating system. And so did Twitter user Brant, We Rate Dog's Reviewer 2. And Brant is right, right? The flaw in the rating system is part of the gimmick of the website, but psychometrically inaccurate.. It would be a funny class exercise to create a rubric for a true rating scale for a dog.
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