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

Okay. I haven't used this in class yet because it is July, and I just found it. However, I will open the Fall 2024 semester with this example. It is fun and accessible and shows how research can be used to study whether or not personality varies based on astrological signs. I will start by showing them a bunch of funny astrology memes (see above). Then, I'll ask them to think of ways to design a study to prove that astrology is/is not bunk. What sort of data would they need to collect to do this?  Then, I'm going to show them this study ( Joshanloo, 2024 ): https://onlinelibrary.wiley.com/doi/epdf/10.1111/kykl.12395?domain=author&token=BKSRDREAX9F3BKAWGVBD Statsy things to share with your students: 1. Archival data : The used repurposed, vintage, federal data. The General Social Survey, to be specific. Data scientists are trained to see the potential of random data sets.    The horoscope sign was simple to determine since the GSS collects birthday data. The author was...

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,...

  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...

OK. Lotte van Rijswijk, writing for Resume.io,  used Instagram photos to determine the happiest college in the United States, United Kingdom, and Australia . Here is the Top 20 list for the US. If you go to the website, you can see similar summaries for the UK and Australian data and an interactive table containing all of the data. Here are some ideas for using it in class: 1. This methodology is pretty interesting. She used smiling recognition software and pictures from Instagram to measure happiness. I think this study would pair well with this study about using software to evaluate smiles: https://journals.sagepub.com/doi/10.1177/0956797617734315 https://resume.io/blog/the-happiest-schools-in-the-us-uk-and-australia 2. Ask your student to consider the sampling error that may result from using Instagram data for any research. For example, are photos on Insta representative of human experiences? Is it reasonable to gather a sample of college-aged students using Insta? 3. The ...

Conflict of interest statement: I am slightly shorter than the average American woman. But I'm adorable, so I score low on the Dark Triad?? This blog post started with me giggling at click-bait headlines, but THEN I realized this is one of those rare articles that use data analyses that we teach in Psych Stats. The journey began when I saw this on Twitter: Hilarious, right? Not to be outdone, the NY Post ALSO needed to cover this study:   https://www.google.com/amp/s/nypost.com/2023/02/27/short-people-more-likely-to-be-psychopaths-study/amp/ I'm wheezing. Immediately, this was a great example of clickbait reporting. The research used The Dark Triad as the theoretical underpinning, and The Dark Triad is like what Mindfulness was 10 years ago in psych research. It is just everywhere. BUT...then I realized this is a very easy-to-read study that you could share with advanced UGs, no problem. What does the original research state? https://www.sciencedirect.com/science/article/pii/S...

Ages ago, I shared how I teach ANOVA at a conceptual level. I describe within and between group variance using beliefs about the human role in climate between and within different religious groups. This data is now old. And it described global warming, not climate change, which is a crucial language distinction. So you  can imagine my delight when Pew recently released  updated and improved data investigating this issue.  In my attempt to keep the mood light when discussing an example featuring 1) religion, 2) climate change, and 3) politics, I ask students to think about how many different opinions are probably represented around their family's Thanksgiving table. Despite having much in common as a family, like, perhaps, geography, shared stories, and religion, there are still a lot of within-group differences of opinion. This leads to a discussion about people of different religions having between and within group differences of opinion regarding beliefs about global cl...

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...

Twitter is my muse. This blog post was inspired by this Tweet:    In a study comparing blood concentrations of caffeine after coffee or energy drink consumption, blood caffeine levels peaked at about 60 minutes in all conditions. Plan accordingly. https://t.co/cWWakGGtHe pic.twitter.com/c5Nn3x3w1f — Kevin Bass (@kevinnbass) November 30, 2021 This study is straightforward to follow. I, personally, think it is psych-friendly because it is about how a drug affects the body. However, it doesn't require much psych theory knowledge to follow this example. Sometimes I'm worried that when we try too many theory-heavy examples in stats class, we're muddying the waters by expecting too much from baby statisticians who are also baby psychologists. Anyway. Here are some things you can draw out of this example: 1. Factors and levels in ANOVA The factor and levels are easy to identify for students. They can also relate to these examples. I wonder if they used Bang energy drinks? They a...

The Pudding  took a data-driven approach to test a popular hypothesis: Women's pockets are smaller than men's pockets.  Authors Diehem and Thomas sent research assistants to measure the pockets on men's and women's jeans. They even shared supplemental materials, like the exact form the RAs completed. https://pudding.cool/2018/08/pockets/assets/images/MeasurementGuide.pdf And they used fancy coding to figure out the exact dimensions of the jeans. Indeed, even when women are allowed pockets (I'm looking at you, dressmakers!), the pockets are still smaller than they are in men's jeans. They came to the following conclusion: Amen. Anyway, there are a few ways you can use this in the classroom: 1) Look at how they had a hypothesis, and they tested that hypothesis. Reasonably, they used multiple versions of the same kind of pants. If you check out their data, you can see all of the data points they collected about each type of jeans. They even provide supplemental mat...

When I teach inferential statistics, I think it is helpful in providing several conceptual (no by hand calculations, no data analyzed via computer) examples of experiments that could be analyzed using each inferential test. I also think it is essential to use non-psychology examples and psychology examples because students need to see how stats apply outside of psychology. At times, I believe that students are convinced that a class called Psychological Statistics doesn't apply outside of psychology.  So I like this quick, easy-to-follow example from medicine. Thomas, Patel, and Bittel (2021) studied how different vitamin supplements affected outcomes for people with COVID-19. The factor (COVID intervention) has four levels (usual care/control, ascorbic acid, zinc gluconate, and ascorbic acid/zinc gluconate). And the four groups acted pretty much the same. Bonus stats content: Error bars, super-cool Visual Summary of a research study that really highlights the most essential parts...

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...

In our stats classes, we need MANY examples to convey both theories behind and the computation of statistics. These examples should be memorable. Sometimes, they can make our students laugh, and sometimes they can be couched in research. They should always make our students think. In this spirit, I've collected three small examples from the Pew Research Center's  Race and Ethnicity  archive (I hope to update with more examples as time permits). I don't know if any data collection firm is above reproach, but Pew Research is pretty close. They are non-partisan, they share their research methodology, and they ask hard questions about ethnicity and race. If you use these examples in class, I think that it is crucial to present them within context: They illustrate statistical concepts, and they also demonstrate outcomes of racism.   1. "Most Blacks say someone has acted suspicious of them or as if they weren't smart" Lessons: Racism, ANOVA theory: between-group dif...

I hope everyone is hanging in there. Here is a pretty straight forward one-way ANOVA example that is interactive, based on for-real personality psychology research, and interesting. I blogged about this previously but whipped up a Google Slideshow you can download and edit to suit your own teaching. Also, I uploaded data that you can use with your students.  TL:DR- A bunch of researchers gave the NEO to 1.5 million Americans to determine if different regions of the US have different personality trends (see research here ).  Original Study They do. Then Time magazine reported on the study . And the scicomm was beautiful. They accurately described the research AND created a fun interactive portion in which you students can take the NEO-Short Form and be matched with the state that best matches their personality (Hi, I am West Virginia because I'm high in neuroticism and low in openness to new experiences, which are great qualities to have during a pandem...

If you, or your students, want to know everything there is to know about ANOVA, you can point them towards this free resource: Tabachnick and Fidel's Experimental Designs Using ANOVA. Access it here: https://www.dropbox.com/s/k3g7kl2h7u3kkwd/ExperimentalDesignsUsingANOVA.pdf And this is a legit, non-exploitive, non-stolen copy of the book. According to this post from the Society for the Teaching of Psychology Facebook group, T&F have decided to share the book freely.

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...

Stick with me here. I think this would be a great warm-up activity early in the semester. My boy Ace had a research hypothesis, operationalized his research, tried to collect data points using several test subjects, and measured his outcomes. Here is the original interview from  Draft Diamonds  and  Newsweek's story . 1) How did he operationalize his hypothesis? What was his IV? DV? 2) Did he use proper APA headers? Should APA style require the publication of pictures of crying researchers if their findings don't replicate? 3) This data could be analyzed using a repeated measure ANOVA. He had various members of his family throw a football as different PSIs and he measured how far the ball traveled and calculated mean for three attempts at each PSI. 4) His only participants were his mom, dad, and sister. So, this study is probably underpowered. 5) In this video from NBC news , Ace's dad describes how they came up with the research idea. Ace i...