Collin's "America’s most prolific wall punchers, charted"

Collin gleaned some archival data about ER visits in America from US Consumer Product Safety Commission. For each ER visit, there is a brief description of the reason for the visit. Collin queried punching related injuries. See his Method section below, which describes how he set the parameters for his operationalized variable. With a bit of explaining, you could also describe how Collin took qualitative data (the written description of the injury) and converted it into quantitative data:

http://qz.com/582720/americas-most-prolific-wall-punchers-charted/

Then he made some charts.

The age of wall punchers is right-skewed. And probably could be used in a Developmental Psychology class to illustrate poor judgment in adolescents as well as the emergence of the prefrontal cortex/executive thinking skills in one's early 20s.

http://qz.com/582720/americas-most-prolific-wall-punchers-charted/

The author looked at wall punching by month of the year and uncovered a fairly uniform distribution.

http://qz.com/582720/americas-most-prolific-wall-punchers-charted/

How to use in class:
-Skew
-Taking qualitative data and coding it (here, turning "ER Visit" into "Wall Punch: Yes or No"
-Uniform Distributions
-Method section
-Archival data
-Criteria for operationlizing a variable when coding data

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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