Use spicy, spicy peppers to explain scales of measurement and/or the difference between categorical and continuous data.

This spicy example explains scales of measurement, continuous vs. categorical variables, and how you can measure and quantify anything.

Uncommon Goods sells quirky gifts. While I was looking for Christmas gifts last year, I came across this kit

https://www.uncommongoods.com/product/scoville-scale-chili-pepper-tasting-kit#618780000000

I have a teenage son, and teen boys love this sort of stuff. Actually, I think spicy peppers are enjoying increased popularity due to the Hot Ones show (The show where celebrities eat increasingly hot chicken wings while being interviewed, like Jennifer Lawrence and her famous GIF from the show).

Maybe you could link this example back to that show? Welcome to how my brain works. Anyway, among the information Uncommon Goods shared about this kit was an image of the packaging for the kit, detailing the Scoville scale rating for each pepper:

And my stats teacher brain translated this packaging into this, since the same data (hottness) is presented in two different ways:

My fellow teachers, please update your favorite examples of basic statistical concepts, like scales of measurement. This can also be a good example for a start-of-class review in which you ask your students to classify the Heat/Pepper/SHU data types. Here are all of my examples for teaching scales of measurement.

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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