Katherine Baicker ,  Oeindrila Dube ,  Sendhil Mullainathan ,  Devin Pope,  and  Gus Wezerek created an interactive, data-driven piece for NYT . It provides a new perspective on how we should proceed with re-opening businesses during the COVID-19 pandemic. They argue that we must consider 1) how long people linger in different types of stores, 2) how often they visit these stores, 3) the square footage of the stores, and 4) the amount of human interaction/surface contact associated with how we shop at different stores.  How to use this in class:    1) Show your students how data can inform real-life problems. Or crises, like how to safely re-open stores during COVID-19. 2) Show your students how data can be used in creative ways to solve problems. The present argument uses cellphone location data. 3) Show your students data viz in real life: Here, scatterplots that really improve the #scicomm potential of this piece. 4) Show your students the rese...

TL:DR: Ameri-centric teaching example ahead: Have your students take this quiz, and the internet will tell them which regions of the US talk the same as them. Use it to teach validity. Longer Version: The NYT created a gorgeous version ( https://www.nytimes.com/interactive/2014/upshot/dialect-quiz-map.html ) of a previously available quiz ( http://www.tekstlab.uio.no/cambridge_survey/ ) that tells the user what version of American English they speak. The prediction is based upon loads and loads of survey data that studies how we talk. It takes you through 25 questions that ask you how you pronounce certain words and which regional words you use to describe certain things. Here are my results: Indeed, I spent elementary school in Northern Virginia, my adolescence in rural Central PA, college at PSU, and I now live in the far NW corner of PA. As this test indeed picked up on where I've lived and talked, I would say that this is a  valid  test based just on my u...

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...

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 ;)

The New York Time's maintains The Learning Network, which contains news content that fits well into a variety of classrooms teaching a variety of topics.  Recently, they shared a good stats example. They created curves illustrating global climate change over time. The top graph illustrates a normal curve, with normal temperature as the modal value. But as we shift forward in time, hot days become modal and the curves no longer overlap. Sort of like the classic illustration of what a small to medium effect size looks like in terms of distribution overlap.  This graph is part of the NYT's "What's going on in this graph?" series , which are created and shared in partnership with the American Statistical Association.

As I've discussed in this space before, I think that it is just as important to show our students how to use statistics in real life as it is to show our students how to conduct an ANOVA. The "You Draw It" series from the New York Times provides an interactive, personalized example of using data to prove a point and challenge assumptions. Essentially, this series asks you to predict data trends for various social issues. Then it shows you how the data actually looks. So far, there are three of these features: 1) one that challenges assumptions about Obama's performance as president, 2) one that illustrates the impact of SES on college attendance, and 3) one that illustrates just how bad the opioid crisis has become in our country. Obama Legacy Data This "You Draw It" asks you to predict Obama's performance on a number of measures of success. Below, the dotted yellow line represents my estimate of the national debt under Obama. The blue line shows t...

Alright, stick with me. This article is about marijuana dosage  and it provides good examples for how researchers go about quantifying their variables in order to properly study them. The article also highlights the importance of Subject Matter Experts in the process and how one research question can have many stakeholders. As the title states, the main question raised by this article is "How much weed is in a joint?". Why is this so important? Researchers in medicine, addictions, developmental psychology, criminal justice, etc. are trying to determine how much pot a person is probably smoking when most drug use surveys measure marijuana use by the joint. How to use in a statistics class:

UPDATE, 9/22/22: Here is a non-paywalled link to this information:  https://www.nytimes.com/2017/10/09/learning/whats-going-on-in-this-graph-oct-10-2017.html This article from the NYT is based on a survey . That survey asked a bunch of nutritionists if they considered certain foods healthy. Then they asked a bunch of everyday folks if they considered the same foods to be healthy. Then they generated the percentage of each group that considered the food healthy. And the NYT put the nutritionist responses on a Y-axis, and commoners on the X, and made a lovely scatterplot... Nutritionists and non-nutritionists agree that chocolate chip cookies are not healthy. However, nutritionists are far more critical of American cheese than are non-nutritionists.  ...and provided us with the raw data as well.

I love research that is counterintuitive. It is interesting to me and makes a strong, memorable example for the classroom. That's why I'm recommending Carroll's piece  from the NYT. It questions the conventional wisdom that breakfast is the most important meal of the day. As Carroll details, there is a long standing and strong belief in nutrition research claiming that breakfast reduces obesity and leads to numerous healthy outcomes. But most nutrition research is correlational, not causal. AND there seems to be an echo-chamber effect, such that folks are miss-citing previous nutrition research to bring it in line with the breakfast research. Reasons to use this article as a discussion piece in your statistics or research methods course: -Highlights the difference between correlation and causation -Provides an easy to understand example of publication bias ("no breakfast = obesity" is considered a fact, studies that found the opposite were less likely to...

This obituary for Dr. Frances Oldham Kelsey that tells an important story about research ethics, pharmaceutical industries, and the importance of government oversight in the drug creation process ( .pdf here ). Dr. Kelsey, receiving the President's Award for Distinguished Federal Civilian Service (highest honor given to federal employees) Dr.  Kelsey was one of the first officials in the United States to notice (via data!) and raise concerns about thalidomide , the now infamous anti-nausea drug that causes terrible birth defects when administered to pregnant women. The drug was already being widely used throughout Europe, Canada, and the Middle East to treat morning sickness, but Dr. Kelsey refused to approve the drug for widespread use in the US (despite persistent efforts of Big Pharm to push the drug into the US market). Time proved Dr. Oldham Kelsey correct (clinical trials in the US went very poorly), and her persistence, data analysis, and ethics helped to limit the ...

How do we count the number of poor people in America? How do we operationalize "poor"? That is the psychometric topic of this opinion piece from the New York Times  ( .pdf of same here ). This article outlines several ways of defining poor in America, including: 1)"Jencks’s methodology is simple. He starts with the official 2013 United States poverty rate of 14.5 percent. In 2013, the government determined that 45.3 million people in the United States were living in poverty, or 14.5 percent of the population.Jencks makes three subtractions from the official level to account for expanded food and housing benefits (3 percentage points); the refundable earned-income tax credit and child tax credit (3 points); and the use of the Personal Consumption Expenditures index instead of the Consumer Price Index to measure inflation (3.7 percentage points)." 2)  " Other credible ways to define poverty  paint a different picture. One is to count all those living ...

One way to engage students in the classroom is by bringing in debates and real world examples. Sometimes, such debates take place largely over social media. A Facebook question du jour: Is "free-range" (letting your kids go out side, walk to the store, etc. without supervision) a good way to build independence or child neglect? Anecdotes abound, but how safe is your kid when they are out on their own? What kind of data could help us answer this question objectively? http://www.nytimes.com/2015/03/20/opinion/the-case-for-free- range-parenting.html The first piece of information comes from an opinion piece by Clemens Wergin from the New York Times ( .pdf in case of pay wall). Wergin describes how free range parenting is the norm in Germany and contrasts American attitudes to German attitudes, providing a quick example of multicultralism (and why we should never assume that the American attitude towards something is the only opinion). He then  provides data that explain...

NEVER MIND ABOUT THIS ONE, GUYS! https://hal.sorbonne-universite.fr/hal-01580259/file/Dragicevic_Jansen_2017.pdf (Note the second author). ___________________________________________________________ Wolfers (writing for the New York Times) summarizes a study from  Wansink and Tal  (2014) in which participants were either a) presented with just  in-text data about a drug trial or b) the text as well as with a bar graph that conveyed the exact same information. The results can be read below: Wolfers/NYT According to Wansink and Tal, the effects seem to be strongest in people who agreed with the statement "I believe in science". So, a graph makes a claim more "sciencier" and, therefore, more credible? Also, does this mean that science believers aren't being as critical because they already have an underlying belief in what they are reading?  I think this is a good way of conveying the power of graphs to students in a statistics class as well ...

A study performed by The Public Religion Research Institute  used either a) a telephone survey or b) an anonymous web survey to question people about their religious beliefs and religious service habits. The researchers found that the telephone participants reported higher rates of religious behaviors and greater theistic beliefs. The figure below,  from a New York Times summary of the study , visualizes the main findings. The NYT summary also provides figures illustrating the data broken down by religious denomination. Property of the New York Times Participants also vary in their reported religious beliefs based on how they are surveyed (below, the secular are more likely to report that they don't believe in God when completing an anonymous online survey). Property of Public Religion Research Institute  This report could be used in class to discuss psychometrics, sampling, motivation to lie on surveys, social desirability, etc. Additionally, the sour...

The Central Limit Theorem, explained using bunnies and dragons . Brilliant. I don't use this to introduce the topic, but I do use it to review the topic. Property of Shu-Yi Chiou