Another recent publication with lots of Psych Stats-friendly data analysis

Alright, kismet, coincidence, I don't know. Still, I'm noticing all of these recent and good scientific articles contain the types of statistical analyses we typically teach in Psych Stats.

Like this article:

Hatano, A., Ogulmus, C., Shigemasu, H., & Murayama, K. (2022). Thinking about thinking: People underestimate how enjoyable and engaging just waiting is. Journal of Experimental Psychology: General. Advance online publication. https://doi.org/10.1037/xge0001255

TL;DR: People think they won't enjoy being alone with their thoughts. BUT THEY DO, as the authors demonstrated throughout five experiments. And those experiments contained a bunch of t-tests (and open data). There are even a couple of ANOVAs in there.
This is a fine example of how to flesh out a hypothesis using a multi-study design. And it is a round-about way of making our students (and ourselves) reflect on how we feel about boredom, alone time, and technology.

It also contains some very effective data visualization (and also some effective tables):

A data visualization for Experiment 5, featuring error bars, violin plots, and participant-by-participant plotting.

Will you look at that? A simple research design, with a simple t-test, but visualized very well to demonstrate variability. I feel like these participant-by-participant level illustrations are more honest.

A table containing findings from Study 3 of the experiment.

Maybe data viz. isn't your thing, or what you are teaching a bunch of junior statisticians? No problem, there are also several great tables in this research.

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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