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...
TL;DR: Birds fly away from men a bit sooner than they fly away from women. Full stop.
Here is the original article, and here is a write-up from Nautilus. I love bird research. I'll get into why below. For now, let me show you how to use this example to teach three different lessons in a stats class.
1. Independent t test example with a data set
The researchers shared their data.
The researchers didn't analyze this data with a t test. But they did share this data visualization that looks a whole lot like one:
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| Damn, I love the new trend of the box/violin/jitter plot. |
FYI: Researcher gender/the IV is labeled "gender," and how far the birds were before they flew away/the DV is labeled "FID" (flight initiation distance). Also, I love this example because the data violate the assumption of equal variance and provide a case for discussing Welch's test.
2. Conceptual example for Factorial ANOVA
This example pairs well with a previous blog post featuring data suggesting that gulls take longer to approach a plate of French fries (DV, measured in seconds) when a human is staring at them, compared with when the human is not (IV).
As such, you could walk your students through this as a factorial ANOVA.
How so? Well, you could ask your students to imagine a replication that combines the two studies.
a. What would be a good IV (FID? time to approach the fries)?
b. What are the cells of this design (M/stare at, M/stare away, F/stare at, F/stare away)?
c. What sort of interaction would you expect (they should probably guess something about how birds might be faster to approach a male staring away from the gull than any other group)?
3. Show your students that lots of research is used in a lot of ways you didn't even think possible.
Okay, I'm an Air Force brat. My dad was stationed at the Pentagon for a few years in the 80s. I will never forget when he told me that there were offices at the Pentagon dedicated to studying birds, and figuring out how to keep them from downing very, very expensive USAF aircraft.
I don't think any information is wasted, and I think a lot of it is out there, waiting to be used in novel ways. Bird behavior research doesn't just live in some obscure research journal; it keeps members of the military safe and ensures taxpayers don't have to replace very expensive planes.
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.