Chris Wilson's "Find out what your name would be if you were born today"

This little questionnaire will provide you with a) the ordinal value of your name for your sex/year of birth and then generate b) a bunch of other names from various decades that share your name's ordinal. Not the most complex example, but it does demonstrate ordinal data.

Me and all the other 4th most popular names for women over the years.

Additionally, this data is pulled from Social Security, which opens up the conversation for how we can use archival data for...not super important interactive thingies from Time Magazine? Also, you could pair up this example with other interactive ways of studying baby name data (predicting a person's age if you know their name, illustrating different kinds of data distributions via baby name popularity trends) in order to create a themed lesson that would correspond nicely to that first/second chapter of most undergraduate stats textbooks in which you learn about data distribution and different types of data.

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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. ...

If your students get the joke, they get statistics.

Gleaned from multiple sources (FB, Pinterest, Twitter, none of these belong to me, etc.). Remember, if your students can explain why a stats funny is funny, they are demonstrating statistical knowledge. I like to ask students to explain the humor in such examples for extra credit points (see below for an example from my FA14 final exam). Using xkcd.com for bonus points/assessing if students understand that correlation =/= causation What are the numerical thresholds for probability? How does this refer to alpha? What type of error is being described, Type I or Type II? What measure of central tendency is being described? Dilbert: http://search.dilbert.com/comic/Kill%20Anyone Sampling, CLT http://foulmouthedbaker.com/2013/10/03/graphs-belong-on-cakes/ Because control vs. sample, standard deviations, normal curves. Also,"skewed" pun. If you go to the original website , the story behind this cakes has to do w...

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