9% of Americans think they could beat a crocodile in a fight. What?

https://today.yougov.com/topics/lifestyle/articles-reports/2021/05/13/lions-and-tigers-and-bears-what-animal-would-win-f

Sorry that I haven't been posting as often lately. You would think that with the summer, I would have more flexibility, but I am working hard on some writing deadlines (for a stats textbook!), and my kids' activities have picked up considerably with soccer season starting.

This example illustrates fun data visualizations as well as a t-test.

YouGov is a polling company, sort of like Gallup. They collect many Very Serious polls and silly polls like this one, where they asked participants to state whether or not they could beat 34 different animals (from rats to grizzly bears) in an unarmed fight. Their graphic designer deserves a raise for this bar graph, including several tragic humans vs. animal memes/movie clips.

Here are a few lessons you can draw out of this funny data.

Paired t-test example: They took the participants identified as men and women and graphed out the data. Which is sort of fascinating. There is a good 6-8% of women who I wouldn't cross. I, personally, don't think they could beat a grizzly bear, lion, elephant, gorilla, and crocodile in a fight, but THEY think they could. I bet they do Cross-Fit.

Anyway, this data also serves as a very significant paired t-test. Here is the data.

Even silly studies need a method section! When we teach, we need to show our students good and proper methods sections, but this funny one would be a great introduction to APA sections. I find that the memorable examples tend to stick better.

Weighted vs. Unweighted polling data: YouGov also shared a paper report of the data, which you may find a use for in class. It mentions weighted and unweighted totals, which you could use to open up a discussion about polling techniques that help ensure representativeness.

A table for the rat data from YouGov, found here: https://docs.cdn.yougov.com/07vgk5e81j/YouGov%20-%20Human%20vs%20animal%20fight.pdf

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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