I love dragging on bad science reporting as much as anyone, but I must give All Of The Credit to the Washington Post and its excellent, data-centered reporting on the opioid epidemic . It is a thing of beauty. How to use in class: 1) Broadly, this is a fine example of using data to better understand applied problems, medical problems, drug problems, etc. 2) Specifically, this data can be personalized to your locale via WaPo's beautiful, functional website . 3) After you pull up you localized data, descriptive data abound...# of pills, who provided them, who wrote the scripts (y'all...Frontier Pharmacy is like two miles from my house)...   4) Everyone teaches about frequency tables, right? Here is a good example: 5) In addition to localizing this research via the WaPo website, you can also personalize your class by looking for local reporting that uses this data. For instance, the Erie newspaper reporter David Bruce reported on our local problem ( .pdf of the...

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.

The U.S. Department of Health and Human Services produced a bunch of great videos to explain topics related to human subject research . The videos were created as part of a broader outreach effort intent on  explaining the research process to research participants .  I think they would fit right into a Research Methods course. Topics include: IRBs: Research design: There is also a specific video explaining social science research: All of the videos (along with handouts) are available here . All videos have closed-captions as well as Spanish versions

Malaika Handa , Amber Thomas , and Jan Diehn created a beautiful, interactive website, Colorism in High Fashion . It used machine learning to investigate "colorism" at Vogue magazine. Specifically, it delves into the differences, over time, in cover model color but also how lighting and photoshopping can change the color of the same woman's skin, depending on the photo. There are soooo many ways to use this in class, ranging from machine learning, how machine learning can refine old psychology methodology, to variability and within/between-group differences. Read on: 1. I'm a social psychologist. Most of us who teach social psychology have encountered research that uses magazine cover models as a proxy for what our culture emphasizes and values ( 1 , 2 , 3 ). Here, Malaika Handa, Amber Thomas, and Jan Diehn apply this methodology to Vogue magazine covers. And they take this methodology into the age of machine learning by using k-means cluster and pixels to deter...

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...

This is a fine example of using misleading statistics to try and make an argument. USA Today tweeted out this graphic , related to some data that was collected by some firm. There appear to be a number of method issues with this data, so a number of ways to use this in your class: 1) False Dichotomy:  Survey response options should be mutually exclusive. I think there are two types of muddled dichotomies with this data: a) What is "essential"? When my kids were younger, I had an online subscription for diapers. Those were absolutely essential and I received a discount on my order since it was a subscription. However, according to this survey dichotomy, are they an indulgence since they were a subscription that originated online. b) Many purchases fall into multiple categories. Did the survey creators "double-dip" as to pad each mean and push the data towards it's $18K conclusion? Were participants clear that "drinks out with frien...

You know how every few months, someone Tweets about stock photos that are generated when you Google "professor"? And those photos mainly depict white dudes? See below. Say "hi" to Former President and former law school professor Obama, coming it at #10, several slots after "novelty kid professor in lab coat". Well, Pew Research decided to quantify this perennial Tweet, and expand it far beyond academia. They used Machine Learning to search through over 10K images depicting 105 occupations and test whether or not the images showed gender bias.  How you can use this research in your RM class: 1. There are multiple ways to quantify and operationalize your variables . There are different ways to measure phenomena. If you read through the report, you will learn that Pew both a) compared actual gender ratios to the gender ratios they found in the pictures and b) counted how long it took until a search result returned the picture of a woman for a given j...

Question-wording matters, friends! This example shows how question order and question-wording can affect participant response. This is a good example for all of your research methods and psychometrics students to chew on. Pew Research asked people if they believed in evolution . They did so in three different ways, which lead to three different response patterns. 1) Prior to asking about evolution, the asked whether or not the participant believes in God. 2) Asked participants if they believed in evolution. If they said "yes", they asked the participant whether or not they believe that a higher power guides evolution. 3) They asked participants if they believed in evolution and gave participants three response options:     a) Don't believe in evolution.     b) Believe in evolution due to natural selection.     c) Believe in evolution guided by a higher power. Responses to Option 1: Responses to Options 2. and 3. Oh, the classroom discus...

Legit funny, but also a gentle way to remind our students that Word will not flag a correctly spelled word that is not the word you want.

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.

1) I disagree with Marc Stein's title  for this article. I don't think NBA great Steven Curry's devotion to his favorite snack is a problem. I think it is a very, very endearing example of someone who knows themselves, knows what works for them, and embraces it. A quote from the article describing Curry's popcorn devotion: 2) Curry loves popcorn so much that at the behest of the New York Times, Curry rated popcorn served at all of the pro-basketball arenas: Here is an example of the assessment form:  And here are the results of the NYT's n=1 study. In addition to a statistics class example, I think this could also be used in an I/O class to explain Subject Matter Experts ;)

While I was attending the Teaching Institute at APS, I attended Wind Goodfriend's talk about using case studies in the classroom. Which got me thinking about fun case studies for statistics. But not, like, the classic story about Guinness Brewery and the t-test . I want case studies that feature a regular person in a regular job who used their personal expertise to deduce from data to do something great. An example popped into my head while I was walking my dog and listening to the Hamilton soundtrack: Hercules Mulligan. Okieriete Onaodowan, portraying Hercules Mulligan in Hamilton He was a spy for America during the American Revolution. He was a tailor and did a lot of work for British military officers. This gave him access to data that he shared through a spy network to infer the timing of British military operations. Here is a better summary, from the CIA:  I like this example because he wasn't George Washington. And he wasn't Alexander Hamilton. He had t...

NOTE: SPOILERS ABOUND. The Good Place is on NBC. And I love it.  At the heart of the show is one demon's (Michael) efforts to create a new version of hell that is only hellish because every person is already being punished by who and what they are. Right, I know. Anyway, in Season 3, Episode 11, Michael's bosses argue that this hell isn't working because it actually leads to self-improvement and fulfillment for everyone is supposed to be tormented. And the bosses argue that the self-improvement is a fluke. So one of the other characters, a philosopher named Chidi, suggests...SCIENTIFIC REPLICATION!! The whole episode is great, but here are some screenshots to get started.