The Science of Scare project, conducted by MoneySuperMarket.com, recorded heart rates in participants watching fifty horror movies to determine the scariest of scary movies. Below is a screenshot of the original variables and data for 12 of the 50 movies provided by MoneySuperMarket.com: https://www.moneysupermarket.com/broadband/features/science-of-scare/ https://www.moneysupermarket.com/broadband/features/science-of-scare/ Here is my version of the data in Excel format . It includes the original data plus four additional columns (so you can run more analyses on the data): -Year of Release -Rotten Tomato rating -Does this movie have a sequel (yes or no)? -Is this movie a sequel (yes or no)? Here are some ways you could use this in class: 1. Correlation : Rotten Tomato rating does not correlate with the overall scare score ( r = 0.13, p = 0.36).   2. Within-subject research design : Baseline, average, and maximum heart rates are reported for each film.   3. ...

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:

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...

  The unstoppable pop of Taylor Swift (reuters.com) Here are some ideas for using this to teach statistics: Data visualizations and visualization guides: With cats, y'all. And the Taylor Swift handwriting font. I love the whole vibe of this as well as how they explain their data visualizations. Operationalizing things: The page describes three Spotify metrics for music: Acousticness, danceability, and emotion. The data visualization contains a numeric value for each metric and a description of the metric's meaning. DATA!: Okay. This is an excellent example of things already. And it is delightful. Then I thought, "Oh, wouldn't it be fun if this was in spreadsheet form!" (I think that A LOT, friends). But, as I write a book and my syllabi, I don't have time for that,  BUT A REDDITOR DID HAVE TIME FOR THAT . Dr. Doon created a spreadsheet with 18 columns of Spotify data for each son. It doesn't include the Midnights data but is still a fantastic amount of dat...

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 effe...

 You have to walk before you can run, right? The basics we teach in Psych Stats help our students walk, but they are not typical of published psychology research. It is difficult for Psych Stat instructors to find good examples of our analyses in recently published research (for an exception, check out Open Stats Lab ). A recent publication caught my eye because I love sending people mail ( scroll down to find my list of recommended, envelope-friendly surprises ).  Liu, P. J., Rim, S., Min, L., & Min, K. E. (2022). The surprise of reaching out: Appreciated more than we think. Journal of Personality and Social Psychology , No Pagination Specified-No Pagination Specified. https://doi.org/10.1037/pspi0000402 Spoiler alert: People love being surprised by mail. Like, more than the sender thinks the receiver will be surprised. I was delighted to discover that this interesting paper consists of multiple studies that use what we teach in Psych Stats. Check out this article s...

So, the Journal of the American Medical Academy publishes v isual abstracts  for some of its research articles. I've written about them before (in particular, this example that illustrates an ANOVA ). These abstracts succinctly summarize the research. They feel like an infographic but contain all of the main sections of a research paper. They are great. They quickly relate the most essential parts of a research study and have a home in Intro Stats.  I love them in Psych Stats and use them for several reasons. 1. Using medical examples reminds Psych Stats students that Psych Stats is really Stats Stats, and stats are used everywhere. 2. These are simplified real-world examples. JAMA creates these to help highlight essential facts for journalists and the public, so Intro Stats students are more than ready to take these on. 3. I like to use these as a quick review of some of the inferential tests we teach in stats. This is no guarantee that basic stats were used in the project, b...

A man after my own heart. This is of minimal educational value but maximal stats humor. David purchased a Pure Drink water bowl for his cat. He wanted to know if it actually resulted in his cat drinking more water.  This wee (hahahaha) little study could be used on the first day of class to demonstrate: 1) A hypothesis 2) Operationalized variables 3) Within-subject research design  4) p (HAHAHAHHA)-values 5) What a god damn stats nerd their instructor is 6) The power of data visualization

 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.

This is a beautiful story from Reddit, with a very kind Redditor, Higgnenbottoms/Quoc Tran, who shared his data with all of us, so we can use this as an example of a) independent t-tests, b) violin plots, AND R.  So, user r/quoctran98  wanted to know if Daves knew more Daves than non-Daves do. HA! He started by collecting data from r/samplesize .  Do you all know about that subreddit, where you can post a survey and see who responds? You're welcome. Anyway, Quoc analyzed his data AND created a violin plot to illustrate his data. He shared it at r/dataisbeautiful , which is another excellent stats subreddit. See below. AND...here is the kicker...I contacted Quoc, and he shared his data (so your students can run their t-tests) AND his R code . I cleaned up his data a bit to provide the same results as the graph above (he had someone report that they knew 69 Daves. I mean, he collected the data from Reddit users.).

I started this blog with the hope of making life easier for my fellow stats instructors. I share examples and ideas that I use in my own classes in hopes that some other stats instructor out there might be able to incorporate these ideas into their classes. As we crash-landed into the online transition last Spring, I created took some of the blog posts and made them into lengthier class lessons, including Google Slides and, when applicable, data sets shared via my Google Drive. I ended up with four good lessons about the four big inferential tests typically cover in Psych Stats/Intro Stats: T-test, ANOVA, chi-square, and regression. I think these examples serve as great reviews/homework assignments/an extra example for your students as they try to wrap their brain around statistical thinking. As we are preparing for the Fall, and whatever the Fall brings, I wanted to re-share all of those examples in one spot. Love, Jess ANOVA https://notawfulandboring.blogspot.com/2020/04/online-day-6...

TL:DR: Imma send my students to YouTube to watch three MythBuster clips that approximately illustrate t-test research designs. Then, they will identify the t-test research design that is illustrated by each of these clips.  More detail. MythBusters is a show that gleefully creates research to test urban legends and random questions that arise in day to day life. The questions that my clips tackle are: a) how badly do people drive when distracted by hands-free cell phones, b) could Indiana Jones have really made it through the chamber at the beginning of Temple of Doom and c) what is faster: Weaving in and out of lanes or staying in the right-hand lane when driving? So, they will watch the clips, and I will ask them questions (they will submit their answers via Google Forms Quiz) to make sure they can tell which sort of t-tests you would use to analyze the data, given research design. Here is the PPT I will use. I've never used this exact clip in class before. I di...

Mother Jones' magazine maintains a database of mass shooting events in the United States. 25 variables are collected from every shooting MJs collects 25 variables from every shooting. Below, I've included their own description of the purpose of their database: How to use in class: Within this data is an example for every test we teach in Introduction to Statistics. Correlation/Regression Fatalities Injuries Age of shooter Year of shooting Chi-square Shooter gender Shooter ethnicity Mass or Spree shooting Were the weapons obtained legally? ANOVA Shooter ethnicity T-test Mass or Spree shooting Were the weapons obtained legally? Data Cleaning  Some of these columns need some work before analysis. For instance, there are multiple weapons listed under "Weapon Type". Which is reasonable, but not helpful for descriptive data. You could walk your students through the process of recoding that column into multiple columns. You could also expl...

I have spent many a summer day at Rehoboth Beach, DE. The seagulls there were assholes. They would aggressively go after food, especially your bucket of Thrasher's french fries. Apparently, this is a global problem, as a group of stalwart researchers in the UK attempted to dissuade gulls from stealing french fries by staring those sons-of-a-gun down . Researchers Goumas, Burns, Kelley, and Boogert shared their data . And it makes for a nice t-test example. 1. The Method section is hilarious and true. 2. Within-subject design: Each seagull was observed in the stare down and non-staredown condition 3. Their figure is a nice example of the data visualization trend of illustrating individual data points. 4. The researchers shared their data. You can download it here . The Goumas et al. supplemental data can be used as a paired t-test example, t (18) = 3.13, p = .006, d = 0.717.

Xkcd is a gift to Statisitcs instructors . Author Randall Monroe shares his humor and statistics knowledge. I think that many of his comics can be used as extra credit points , in that you don't get the joke unless you get the conceptual statistical knowledge behind the joke. NOTE: I have included images here, but you really, really should go to the original comics and cursor over for the messages to view the alternative text. NOTE TWO: This is not a comprehensive list but I will try to update it as Monroe shares more comics. To teach APA formatting: https://xkcd.com/833/ To explain sufficient sample size in research: https://xkcd.com/507/ To explain good statistics manners/how to appropriately ask for stats help: https://m.xkcd.com/2116/ To explain error bars: https://xkcd.com/2110/ T-test and the t-curve: https://xkcd.com/2110/ Linear relationships: https://xkcd.com/605/ The Normal Curve: https://xkcd.com/2118/ Cherry picking, p-...