My friends, winter is coming. Winter in Erie, PA, is no joke, so I've been encouraging my kids to pick up inside hobbies. My youngest is all about flipbooks right now, which inspired me to create my own statsy flipbook: Which, in turn, inspired me to create a blog post about statsy crafts. Crafts that you can do over Winter break for fun or maybe use as assignments for your students? A DIY Christmas gift for your favorite statistician?  The flipbook idea is an easy one to implement, as you only need index cards, a binder clip, and a pencil. Actually, many these can be done on the cheap if you have Legos, paper and pen, a log, yarn, baking supplies around. Not free, but not too expensive, either.  Data visualization via knitting A knitting-data-visualizer tracked temperatures via a knitting project, seen below. The different colors of yarn represent different temperatures on different days. Here is a full article from Gizmodo , which includes a link where you can purchase suppl...

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.

Josh Katz and Kevin Quealy p ut together a cool interactive website to help users better understand their NYC commute . With the creation of this website, they also are helping statistics instructors illustrate a number of basic statistics lessons. To use the website, select two stations... The website returns a bee swarm plot, where each dot represents one day's commuting time over a 16-month sample.   So, handy for NYC commuters, but also statistics instructors. How to use in class: 1. Conceptual demonstration of the sampling distribution of the sample mean . To be clear, each dot doesn't represent the mean of a sample. However, I think this still does a good job of showing how much variability exists for commute time on a given day. The commute can vary wildly depending on the day when the sample was collected, but every data point is accurate.  2. Variability . Here, students can see the variability in commuting time. I think this example is e...

Someone on Reddit posted this cool picture of a...contraption? I'll go with contraption. Anyway, it automatically generates a chart of the amount of sunlight per day by burning a log. A Twitter follower recognized this as a Campbell-Stokes recorder . This is beautiful art and data visualization from Hood-Glen Park in San Francisco. How to use in class: 1) Make a bunch of really dumb log arithm jokes. 2) A nice introduction to data visualization. Maybe this could be paired with more traditional sources of weather data. 3) Also makes me think of other naturally occurring charts: Also, while less pretty, think about all the data that is automatically created every time Google Maps identifies your location (and then warns everyone using Google Maps to avoid traffic slowdowns) or Netflix provides you with recommendations based on viewing habits. The Campbell-Stokes recorder could serve as a metaphorical segue into a discussion about all the automated data collectio...

We already knew that model/cookbook author  Chrissy Teigen is really good at Twitter. We recently learned that, delightfully, she is also good at spotting misrepresented statistics. This came to light when she asked for help understanding the whole Jacob Wohl Debacle . She asked her Twitter followers for a clear, quick explanation of the whole deal. She didn't even @ Jacob, but Jacob got snippy and replied back with Google Trends data (how have I not blogged about Google Trends yet?) in an attempt to use data, beautiful data, in order to own Chrissy. And Chrissy was having none of it.  Yes, her sweet burn is an inspiration to us all, but it also a good demonstration of that fact that the exact same data can be interpreted in two different ways. And jerks lie with data, too, and can lie with actual, truthful data. And Chrissy knows her way around a chart.

Here are a bunch of Statsy GIFs. I did not create any of these but I love them all. https://www.instagram.com/linski101/ https://www.instagram.com/linski101/ https://www.instagram.com/linski101/ CI for regression lines: https://twitter.com/ClausWilke/status/1034492581588156416