Mr. Beast gave us a real-life bee swarm plot.

Hey, I have kids, so I knew that Mr. Beast made a video where 100 competitors, one person from every age from 1-100, competed in feats for $250K.

In the very first competition, competitors ran a footrace, and the top five in each age category advanced to the next round.

Image from: https://www.reddit.com/r/data_irl/comments/1r15ecq/data_irl/

Anyway, in doing so, Mr. Beast inadvertently created a jitter plot using humans. Age group/starting line is at the top of the image, with the checkered finish line at the bottom. The dark blue/light blue columns are a nice touch, too.

How to use in class:

1) Pander to your students by using a Mr. Beast example.

2) Ask your students to interpret the data.

What can be learned from this image? The basics of bee plots. As expected, the 11-20, 21-30, and 31-40 groups ran the fastest. However, I think 31-40 was the slowest of the three groups, with a bit more variability.

3) I guess this would also be a good example of a non-linear relationship, as wee babes can't run very fast.

4) The age data were categorized rather than used continuously. .

Here is a clip of just the jitter plot race, and here is the full video.

Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr. Molly Metz maintains a curated list of hilarious "How you doing?" scales. 2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables. So, I decided to create a post about three ways to use these scales in your stats classes: 1) Teaching the basics of variables. 2) Nominal vs. ordinal scales. 3) Daily check-in with your students. 1. Teach your students the basics...

Leo DiCaprio Romantic Age Gap Data: UPDATE

Does anyone else teach correlation and regression together at the end of the semester? Here is a treat for you: Updated data on Leonardo DiCaprio, his age, and his romantic partner's age when they started dating. A few years ago, there was a dust-up when a clever Redditor r/TrustLittleBrother realized that DiCaprio had never dated anyone over 25. I blogged about this when it happened. But the old data was from 2022. Inspired by this sleuthing, I created a wee data set, including up-to-date information on his current relationship with Vittoria Ceretti, so your students can suss out the patterns that exist in this data.

Tyler Vigen's Spurious Correlations

Tyler Vigen has has created a long list of easy-to-paste-into-a-powerpoint graphs that illustrate that correlation does not equal causation. For instance, while per capita consumption of cheese and number of people who die by become tangled in their bed sheets may have a strong relationship (r = 0.947091), no one is saying that cheese consumption leads to bed sheet-related death. Although, you could pose The Third Variable question to your students for some of these relationships). Property of Tyler Vigens, http://i.imgur.com/OfQYQW8.png Vigen has also provided a menu of frequently used variables (deaths by tripping, sunlight by state) to help you look for specific examples. This portion is interactive, as you and your students can generate your own graphs. Below, I generated a graph of marriage rates in Pennsylvania and consumption of high fructose corn syrup. Generated at http://www.tylervigen.com/

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