Why do post-partum women see faces everywhere?

Y'all. This is a statsy example featuring sensation and perception, developmental, and neuroscience.

The study found that post-partum, but not pregnant, women, saw faces where there were no faces (pareidolia illusion). It is attributed to the endogenous oxytocin bump women experience after they have babies. Here is a link to Newsweek's treatment of the study and the actual study.

Here are some examples of the photos used in the experiment. They are so dear because I see faces.

I think my favorite is the clothes washer. Anyway, the researchers used pregnant women, post-partum women, and a control group and measured how often they saw faces.

How to use

1. There is a good ol' Mann-Whitney U in this study. Making this the first ever Mann-Whitney U featured on the blog.

2. The researchers used OSF, and the data is available.

3. I like the growing trend of pairing newer and older data visualizations. Here, bar graphs and jitter plots are used to illustrate the same data, and you can really see how the jitter plot does a better job at conveying variance in the data.

4. The Newsweek coverage is nice because a) there is an audio portion you could play in class and b) the scientists talk about HOW they came to this hypothesis to test. I think young psychologists need to hear more of these stories.

5. There is a factorial ANOVA in there, too.

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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