This YouGov data asked Americans to rate how much they enjoy a variety of summer activities. They graphed out the percentage of people, divided by demographics, who indicated that they like or love a summer activity. One of the demographics they used was age. Which makes me feel seen, and I can already imagine how I will poke fun at myself, a 46-year-old who hates outdoor sports. More  pedagogically, I can use this data when introducing paired  t -tests. Specifically, I can get them to ponder this data and think about why  the age differences exist.   Here is the data visualization for activities where there is a big age gap in enjoyment: Here is the data visualization for activities where there is not a big age difference: I think they really missed out by not including birdwatching on this list. I'm 46 and I hecking love it.  I could also see this as an example in a Developmental or Psychology of Aging course. What is driving the differences between older...

Ok, more Taylor Swift data for you. DID YOU KNOW that Spotify collects buckets and buckets of data about each and every song it provides (see:  https://www.spotify-song-stats.com/about ) So, I downloaded this information for 1989 and 1989 (Taylor's Version). So I could test for any differences between the recordings. Like, with data, not with my feelings and emotions. Specifically with a paired t -test. I get it. The sample sizes are very small. However, the data is still interesting. It makes sense that the tempo hasn't changed. Like, she did slow down or speed up anything. And that is super NS with an itty-bitty effect size. It is also interesting that acousticness has decreased. These are more heavily produced versions of the same songs (IMO), and while this change didn't achieve significance, it is a moderate effect size.  ANYWAY, you aren't really here for this information. You are here for data to share with your classes, yes? I'm here to help you teach your s...

1. I assure you, your traditional college-aged students know who Mr. Beast is. 2. If you don't know who he is, just Google him. 3. His real name is Jimmy so that's what I'll call him for the remainder of the post because while I respect his work and can't handle writing/referring to an adult human who isn't a wrestler as Mr. Beast again. Anyway, Jimmy shared, via Twitter (it is still Twitter) that he had done some A/B testing on his clips. A story in two Tweets.  https://twitter.com/MrBeast/status/1699460698726613343 https://x.com/MrBeast/status/1699460698726613343?s=20 This story made the rounds because Mr. Beast is such a famous YouTuber . How can you use this example in class? 1. Introduce A/B testing, and how some of the techniques used by professional statisticians are actually pretty straightforward application of basic statistics tests (here, paired t -test). 2. Conduct a paired t -test: I made up some pretend data that imitates these findings . 3. Review the...

ASIDE: THIS IS MY 500th POST. PLEASE CLAP. Efficacy data about a mental health intervention? Yes, please. The example has so much potential in a psych stats classroom. Or an abnormal/clinical classroom, or research methods. Maybe even human factors, because three numbers are easy to remember than 10? This post was inspired by an NPR story  by Rhitu Chatterjee. It is all about America's mental health emergency hotline's switch from a 10-digit phone number to the much easier-to-remember three digits (988), and the various ways that the government has measured the success of this change. How to use this (and related material) in class: 1) Assessment. In the NPR interview, the describe how several markers have improved: Wait times, dropped calls, etc.  Okay, so the NPR story sent me down a rabbit hole of looking for this data so we can use it in class. Here is the federal government's website about  988  and a link to their specific  988  performance data,...

 Here is a quick RM review I created for my Psych Stats students. We were preparing for the first exam, which covered the very basics of research methodology, including IVs and DVs. We also talk about data visualizations and how they can be used to quickly convey information.  California is dealing with an energy crisis and a heatwave. California tried a relatively inexpensive intervention to reduce the likelihood of overwhelming the energy grid: Sending out text messages during extremely high energy usage. See:   https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts And what happened? People reduced their electric usage. Source: https://www.bloomberg.com/news/articles/2022-09-07/a-text-alert-may-have-saved-california-from-power-blackouts For the class review, I asked my students to think of the emergency alerts they receive from their university via our campus safety app. I challenged them to think of a c...

 https://today.yougov.com/topics/lifestyle/articles-reports/2021/05/13/lions-and-tigers-and-bears-what-animal-would-win-f Sorry that I haven't been posting as often lately. You would think that with the summer, I would have more flexibility, but I am working hard on some writing deadlines (for a stats textbook!), and my kids' activities have picked up considerably with soccer season starting. This example illustrates fun data visualizations as well as a t-test. YouGov is a polling company, sort of like Gallup. They collect many Very Serious polls and silly polls like  this one, where they asked participants to state whether or not they could beat 34 different animals (from rats to grizzly bears) in an unarmed fight. Their graphic designer deserves a raise for this bar graph, including several tragic humans vs. animal memes/movie clips. Here are a few lessons you can draw out of this funny data. Paired t-test example: They took the participants identified as men and women and...

 Hi, While Blogger does allow me to tag my posts, I thought it might be easier if I just created a compendium for the major sections of Psych Stats? Especially since the search function doesn't work great on mobile devices. And sometimes, you don't want to go poking around and just need to prep for a class fast.  Also, every blessed one of you deserves an Easy Button here in the middle of a pandemic.  And, of course, my mind organizes the world into spreadsheets, so I made a spreadsheet. I hope this helps with your teaching. https://docs.google.com/spreadsheets/d/1b_FcZkJKf5a5M05Jwp62ZJiVYu6s51W2WXve4L8r1MU/edit?usp=sharing PS: Be on the lookout, I'll probably do this for ANOVA, chi-square, regression, correlation, etc.

UPDATE, 9/22/22: Here is a non-paywalled link to this information:  https://www.nytimes.com/2017/10/09/learning/whats-going-on-in-this-graph-oct-10-2017.html This article from the NYT is based on a survey . That survey asked a bunch of nutritionists if they considered certain foods healthy. Then they asked a bunch of everyday folks if they considered the same foods to be healthy. Then they generated the percentage of each group that considered the food healthy. And the NYT put the nutritionist responses on a Y-axis, and commoners on the X, and made a lovely scatterplot... Nutritionists and non-nutritionists agree that chocolate chip cookies are not healthy. However, nutritionists are far more critical of American cheese than are non-nutritionists.  ...and provided us with the raw data as well.