Andi Putt's infographics on autism prevalence demonstrate y-axis truncation and the surveillance effect.

This example illustrates how better assessment has likely increased in autism diagnoses (as opposed to the increase being due to vaccines or hysterical parents). It does a good job of illustrating truncated y-axes and the surveillance effect. It also reminds our psychology majors that we have many professional allies and colleagues outside of psychology. Like speech language pathologists.

I found these examples (see below) on Facebook from speech-language pathologist/excellent science communicator Mrs. Speechie P. AKA Andi Putt.

How to use in class:

1. Truncated y-axis

I like how she mentions that truncated y axes can be a scare tactic. I also like that she shows there are still relatively few in the total population.

https://www.facebook.com/photo/?fbid=1327073175898079&set=a.463959318876140

On this theme, she shared a second image that does a really good job of showing how proper diagnosis isn't the same thing as fake/inflated diagnoses (a common argument in anti-autism/anti-accommodation circles).

https://www.facebook.com/photo?fbid=1326352029303527&set=pb.100057862261072.-2207520000

Y'all, Mrs. P. did the heavy lifting for us. This spells out the dates and explains how psychology/psychiatry groups and adjacent groups improved the assessment and identification of people with autism. Professionals are finally putting a diagnosis on a behavioral phenomenon and treating it more often (AKA the surveillance effect). While I am biased towards my fellow stats teachers, this certainly has a home in your clinical/counseling/developmental/RM classes.

If you like this example, you'll love my textbook, Psychological Statistics for Everyone.

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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