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.

One of my favorite upper-level elective courses to teach is Positive Psychology. I recently came across a comprehensive account of various facets of how positive psychology can be assessed in nations:  https://ourworldindata.org/happiness-and-life-satisfaction . Like, the website is just great. Below is an example of the data you can explore, in various formats, animation options, and you can download the data. It is great! From this website, I download loaded and compiled two data sets that caputure GDP, Cantrill Ladder Score, and life span data for hella countries. You can perform a variety of significant and non-significant correlations and regressions using this data. Additionally, the countries are divided into six regions, allowing you to conduct some one-way ANOVAs with your students.  Here is the data, compiled by my awesome RA, Maddie:  https://docs.google.com/spreadsheets/d/129NQcPdFwZjyzZAJdX6odKC7KiFk_Q1Lqa-SD4kk5FQ/edit?usp=sharing

  You aren't a proper stats nerd if you have not scrolled for an hour through all of  The Pudding's  content .  Thank goodness for The Pudding, which helped me spice up the discussion boards in my online stats class. For a long time, I emphasized rigor over wonder. In my stats class, I had functionally reasonable but not terribly engaging topics for class discussion. That changed last semester. I spiced up my discussion board with some of my favorite data visualizations, like this one about using a fast food app to track power outages after a natural disaster and this one that illustrates data on the efficacy of nutritional supplements in a beautiful and functional way. Here is another that lets students look at trends in art and wonder about how this may reflect on cultural shifts in courting and romantic relationships . TL;DR The Pudding recently shared a post about trends in love songs from 1958 through 2023. The whole interactive is very engaging and lets yo...

I have found plenty of class inspiration on Reddit. Various subs have provided a  new way to explain mode   and median  and great, intuitive data to teach  correlation . However, much as a reverse-coded item on a scale can be used to get to the opposite of what you are asking about, r/DataIsUgly is rife with examples of how NOT to do data as to teach how to create good data visualizations. Very recently, I shared this example from r/DataIsUgly to illustrate why NOT to truncate the Y axis .  And...this sub is filled with people like us. People who love to proofread and notice data crimes. For example: How to use it in class? Can your students figure out why these data visualizations are...less than optimal? Can they fix them? They could be a fun prompt for extra credit points or a discussion board.

Moderation isn't one of those things that we typically teach in Intro Stats. But it is a statistical tool your advanced undergraduates will likely encounter in an upper-level course. I'm not going to teach you how to teach your students how to do one. I am, however, going to share a  example of what mediation is doing, inspired by living in the city in the US that has received the most snow this season (Erie, PA, with 93.9 inches for the season as of 1.30.25).  About a year ago, CNN shared data on how much snow it takes to cancel school in various parts of the country. I assure you, Erie and the rest of Northwest PA (see red outline) gets hella snow but no snow days. https://www.cnn.com/2024/02/12/us/how-much-snow-kids-school-snow-day-across-us-dg/index.html However, our lack of snow days isn't due to lack of snow. The annual amount of snow moderates the likelihood to cancel school, such that if you are used to a lot of snow (and have the infrastructure to handle it) you d...

I maintain that relative versus absolute risk is a concept that we absolutely must teach in intro stats. I have given some examples of this before ( murder ! COVID !) but here is another one that hits home for my fellow Great Lakers. In particular, this one is for my friends in Detroit, Toledo, Cleveland, and Buffalo  Up here in Erie, a common point of discussion is how frozen Lake Erie is. Because once it freezes, the lake's moisture no longer feeds Dread Lake Effect Snow.   I like this example because you can easily perform the math in front of your class, demonstrating that 26.14% is 103.45% of 12.85%. At the same time, you have the visual to demonstrate that the vast majority of the lake was still unfrozen even with a 103.45% increase. 

I can't be the only one teaching online statistics this Spring. Last fall, I refreshed ALL of my discussion boards for my online version of Psychological Statistics. I haven't done so since 2020, and my students responded well to my new discussion topics, all of which are centered in statistical literacy and improving problem-solving with data. My first one is based on this old blog post about how residents of Houston used a Whataburger location map to figure out which parts of Houston were without electricity following Hurricane Meryl. Here is how I presented it to my students: You never know where valuable data visualizations will come from! For instance, following Hurricane Beryl, Texans used the Whataburger app to track power outages across Houston. Whataburger is a popular restaurant chain in the South. Its app has a feature where users can quickly see open or closed locations. Normally, this is used by hungry people to find the closest, open location. HOWEVER: There are S...