Alison Horst: Brilliant data illustrations

As I write this, I am a parent on the first day of summer break, and I have two kids who are very different from one another. So, these hilarious examples of Type I/II error from Alison Horst really speaks to me.

Not only are these illustrations beautiful and funny, but I think they really get your students to think about one HUGE underlying issue in all of inferential statistics: Every little sample that we analyze is just one of near-infinite possible samples that could have been drawn from the underlying population (or, the sampling distribution of the sample mean).

Head over to her GitHub for a funny, normal curve illustration and higher resolution versions of the above pictures. She also has numerous beautiful R and ggplot illustrations.

UPDATE: 11/6/19

Alison made some super cute illustrations for a topic that is simultaneously very boring but also tricky for baby statisticians: Scales of measurement.

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Ways to use funny meme scales in your stats classes

Have you ever heard of the theory that there are multiple people worldwide thinking about the same novel thing at the same time? It is the multiple discovery hypothesis of invention . Like, multiple great minds around the world were working on calculus at the same time. Well, I think a bunch of super-duper psychology professors were all thinking about scale memes and pedagogy at the same time. Clearly, this is just as impressive as calculus. Who were some of these great minds? 1) Dr. Molly Metz maintains a curated list of hilarious "How you doing?" scales. 2) Dr. Esther Lindenström posted about using these scales as student check-ins. 3) I was working on a blog post about using such scales to teach the basics of variables. So, I decided to create a post about three ways to use these scales in your stats classes: 1) Teaching the basics of variables. 2) Nominal vs. ordinal scales. 3) Daily check-in with your students. 1. Teach your students the basics...

Using pulse rates to determine the scariest of scary movies

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. ...

Andy Field's Statistics Hell

Andy Field is a psychologist, statistician, and author. He created a funny, Dante's Inferno-themed web site that contains everything you ever wanted to know about statistics. I know, I know, you're thinking, "Not another Dante's Inferno themed statistics web site!". But give this one a try. Property of Andy Field. I certainly can't take credit for this. Some highlights: 1) The aesthetic is priceless. For example, his intermediate statistics page begins with the introduction, "You will experience the bowel-evacuating effect of multiple regression, the bone-splintering power of ANOVA and the nose-hair pulling torment of factor analysis. Can you cope: I think not, mortal filth. Be warned, your brain will be placed in a jar of cerebral fluid and I will toy with it at my leisure." 2) It is all free. Including worksheets, data, etc. How amazing and generous. And, if you are feeling generous and feel the need to compensate him for the website, ...

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