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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...

Young adult suicide is down, as demonstrated by regression.

This is an article about a very sensitive topic, but it is also a hopeful article (young adult suicide seems to be on the decline in the US, and there is reason to believe that it is due to the introduction of the 988 hotline .) Here is a  link to the original research study published in JAMA Network , and here is a link to  Scientific American's write-up on the research . In my class, I emphasize that regression has a lot in common with correlation, but adds prediction. I emphasize it so much that I used it in the name of my regression chapter in my textbook . As such, I was delighted to find this  excellent, psychology-related example of how past data was used to predict the future. But the future is the present? And the predicted data lives in an alternative timeline where the 988 mental health crisis hotline never existed in America. Anyway, TL;DR: Young adult suicide is on the decline (hooray!!) in America, and this research a) uses fancy regression to demonstrate th...

Statsplanations from Sketchplanations

Two of my very favorite statistics comic sources are  Saturday Morning Breakfast Cereal and XKCD.    I have been following them for years, but more recently, I came across Jono Hey's Sketchplanations . These aren't ha-ha comics as much as they are concise explanations of complex concepts. And some of those explanations involve statistics and would look lovely in your class lectures. This is perfect for those of us who teach JASP and try to explain the dangers of misspelling words used as nominal variables.  Also, he has a few that provide images to go with some of our favorite data quotes: Here are full entries under the comic's  statistics  and  data  tags. If this idea was helpful, you'll probably enjoy my textbook, Psychological Statistics for Everyone . It's basically this blog, but organized into a semester.

One small, psychological ANOVA example you can use in class.

This is just a little one-way ANOVA with three levels. You can use it in class to assess, review, or teach the topic. It comes from the following article by Rivera-Chavez et al . https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2843427 TL:DR- They gathered data and performed a one-way ANOVA that suggests that people with emerging psychosis have glutamate (a neurotransmitter) levels that are higher than both controls and folks who have schizophrenia diagnoses. Even if you aren't an expert on this topic, JAMA's ready to explain the relevance of this study to your students: Reasons why I love this as an example for my novice psychological statisticians: 1. This data is related to psychology, a simple one-way ANOVA with three levels, and was recently published, making it a nice little refresh to my course content. There are other analyses in the article, but here are the ANOVA results. 2. I emphasize that my students learn how to read and write statistical findings, so h...