This is a very brief example to spice up the measures of central tendency lecture. There is a game show in Germany, and one of the rounds of the game show is performing a perfect median split on food. OF COURSE, IT IS A BAVARIAN HOT PRETZEL. The "splitting championship" game is part of a larger video game. Here is the YouTube version and here is the Reddit version, with more deets on the game show. To be clear, we aren't talking about eye-balling here. The median split is an exact split by weight. Just as a statistical median split is an exact splitting of a data set. Here is a more exact screen grab:  ALSO: Because I love a good internet rabbit hole, the Reddit source I found actually goes into detail about the German game show. Have fun. 

Hey, all- Here is today's (2.8.24) presentation  about working more statistics into your social psychology course. I'm mostly posting this for the folks who went to the conference because I told them I would, but feel free to use this advice to add some novel stats examples to your social psychology classes.

Hey!  I'm giving a keynote at the February annual teaching pre-conference at the Society for Personality and Social Psychology conference. It's all about social psychology stats example. Like this one! This one demonstrates social comparison theory without ever saying social comparison theory. YouGov published data  ( here is the full data source ) that asked participants to rate their own, close-other, and far-others on several factors related to modern life (see below). In doing so, they unknowingly trigger social comparison theory, and in particular, downward social comparison. TL;DR: We know ourselves and how well we are doing compared to other people. And people are motivated to feel good about themselves.     https://today.yougov.com/society/articles/48400-americans-compare-own-outlook-with-country-poll These findings smack of downward social comparison, right? Instead of having a specific target we are comparing ourself to, like a co-worker or a neighbor,...

OK. This wasn't my original idea, but I love it so much that I'm blogging about it. The original idea came from Dr. Andrea Sell, who, in turn, got this idea from one of her brilliant student, Johanna Perez.  How t -distributions are like Brazilian Butt Lifts: A treatise.  First, familiarize yourself with the Brazilian Butt Lift: The fat doesn't leave. As illustrated below, the fat just moves...into the tail.  https://ariamedtour.com/blogs/why-is-bbl-popular/ Is this not what William Gosset did when he created the t -curve? Instead of moving around fat, he moved around probability under the normal curve. He moved that probability into the tails . Both Igo Pitanguy (inventor of the Brazilian Butt Lift) and William Gosset (inventor of the t-test) moved things around as to...CREATE A THICKER (thiccer?) TAIL. THIS IS SUCH A PERFECT METAPHOR. See:

I love internet-based teaching ideas. They are free and current. At least they were current when I first posted them, but some of my posts are ten years old.  Such is the case for my old post about the Baby Name Voyage r and how to use it to illustrate unimodal, and bimodal distributions. Instead, please go to NameGrapher to show your students how flash-in-the-plan trendy baby names, like my own, have an unimodal distribution: As opposed to bimodal distributions, which flag a name as a more classical name that enjoyed a resurgence, like Emma: When I use this in class, I frame it between names that were trendy once and names that were trendy one hundred years ago and are again trendy. As a mom to grade-school-aged kids, I have certainly noticed this as a trend in kid names. So many Lilies and Noras!  I also make sure my students understand that this information is gathered via Social Security Administration applications from the federal government, to back up another clai...

 Hey. Most of you have never met me and only read my words on this blog, so I thought it would be fun to share a recording of a talk I gave at Murray State University in October of this year .  Not only do you get to see/hear me in action, I think this talk does a great job of summing up my approach to statistics and what I want my students to get out of my class. If you agree with my approach, may I gently suggest that you sign yourself up to get updates on  my forthcoming WW Norton Psychological Statistics textbook: https://seagull.wwnorton.com/l/710463/2023-10-26/2tp3nt

Spotify generates gobs of data about music.  Most people have seen the end-of-the-year data Spotify generates for each user about their listening patterns . Most people don't know that Spotify also generates a lot of data about individual songs. Some of it is straightforward: tempo, genre, length. However, Spotify also has its own niche way of quantifying songs: Danceability. Accousticness. Here is a whole list of their variables and descriptions from researchers at CMU:  https://www.stat.cmu.edu/capstoneresearch/315files_s23/team23.html What does this mean for a stats teacher? You have access to highly personalizable data sets, rooted in music, with gobs and gobs of variables for each song...or artist...or album...or year of release...or genre (like, so many ways to divide up your data).  For instance,  I created a data set with Spotify data for 1989 and 1989 (Taylor's Version) to teach paired  t -tests . How do Taylor's re-recordings compare to the originals?...