Elahe Izadi, writing for The Washington Post, shared polling data from the 1960s. The data focused on public opinion about different aspects of the civil rights movement (March on Washington, freedom riders, etc.). The old data was used to draw parallels between the mixed support for the Civil Rights Movement of the 1960s and the mixed support for current civil rights protests, specifically, Black Lives Matter. Here is the  Washington  Post  story on the polling data, the civil rights movement, and Black Lives Matter. The story is the source of all the visualizations contained below. H ere is the original polling data . https://img.washingtonpost.com/wp-apps/imrs.php?src=https://img.washingtonpost.com/blogs/the-fix/files/2016/04/2300-galluppoll1961-1024x983.jpg&w=1484 https://img.washingtonpost.com/wp-apps/imrs.php?src=https://img.washingtonpost.com/blogs/the-fix/files/2016/04/2300-galluppoll1963-1024x528.jpg&w=1484 I think this is timely data. And...

Nathan Yau , writing for Flowing Data , provides a good example of correlation, median, and correlation not equaling causation in his story, " Divorce and Occupation ". Yau looked at the relationship between occupation and divorce in a few ways. He used one of variation upon the violin plot to illustrate how each occupation's divorce rate falls around the median divorce rate. Who has the lowest rate? Actuaries. They really do know how to mitigate risk. You could also discuss why median divorce rate is provided instead of mean divorce rate. Again, the actuaries deserve attention as they probably would throw off the mean. https://flowingdata.com/2017/07/25/divorce-and-occupation/ He also looked at  how salary was related to divorce, and this can be used as a good example of a linear relationship: The more money you make, the lower your chances for divorce. And an intuitive exception to that trend? Clergy members.  https://flowingdata.com/2017/07/25/divorce...

So, I am very pro-science, but I have a soft spot in my heart for medical research that improves medical outcomes without actually requiring medicine, expensive interventions, etc. And after spending a week in the NICU with my youngest, I'm doubly fond of a way of helping the littlest and most vulnerable among us. One example of such was published in the journal Pediatrics and written up by NPR . In this case, they found that fewer mistakes are made when not-yet-named NICU babies are given more distinct rather than less distinct temporary names. The unnamed baby issues is an issue in the NICU, as babies can be born very early or under challenging circumstances, and the babies' parents aren't ready to name their kids yet. Traditionally, hospitals would use the naming convention "BabyBoy Hartnett" but several started using "JessicasBoy Hartnett" as part of this intervention. So, distinct first and last names instead of just last names. They measured patie...

The Hedonometer measures the overall happiness of Tweets on Twitter. It provides a simple, engaging example for  Intro Stats since the data is graphed over time, color-coded for the day of the week, and interactive. I think it could also be a much deeper example for a Research Methods class as the " About " section of the website reads like a journal article methods section, in so much that the Hedonometer creators describe their entire process for rating Tweets. This is what the basic table looks like. You can drill into the data by picking a year or a day of the week to highlight. You can also use the sliding scale along the bottom to specify a time period. The website is also kept very, very up to date, so it is also a very topical resource. Data for white supremacy attack in VA In the pages "About" section, they address many methodological questions your students might raise about this tool. It is a good example for the process researchers go ...

I finally have an example of Spearman's rank correlation to share. This is a political example, looking at how Twitter language usage differs in US counties based upon the proportion of votes that Trump received. This example was created by  Jack Grieves , a linguist who uses archival Twitter data to study how we speak. Previously, I blogged about his work that analyzed what kind of obscenities are used in different zip codes in the US . And he created maps of his findings, and the maps are color coded by the z-score for frequency of each word. So, z-score example. Southerners really like to say "damn". On Twitter, at least. But on to the Spearman's example. More recently, he conducted a similar analysis, this time looking for trends in word usage based on the proportion of votes Trump received in each county in the US. NOTE: The screen shots below don't do justice to the interactive graph. You can cursor over any dot to view the word as well as the cor...

I think this is a good first day of class example. It shows how data can make a powerful argument, that argument can be persuasively illustrated via data visualization, AND, maybe, it is a soft sell of a way to keep your students from drunk driving. It also touches on issues of public health, criminal justice, and health psychology. This article from The Economist  succinctly illustrates the decrease in drunk driving incidents over time using graphs. This article is based on a  working paper  by PhD student Jessica Lynn (name twin!) Peck. https://cdn.static-economist.com/sites/default/files/imagecache/640-width/20170408_WOC328_2.png Also, maybe your students could brainstorm third variables that could explain the change. Also, New Yorkers: What's the deal with Staten Island? Did they outlaw Uber? Love drunk driving? 

So, I recently shared a post detailing how to use the Cha-Cha Slide in your Intro Stats class. Today? Today, I will provide you with an example of how to use Kim Kardashian to explain test validity. So. Kim Kardashian-West stumbled upon a Buzzfeed quiz that will determine if you are more of a Kim Kardashian-West or more of a Chrissy Teigen . She Tweeted about it, see below. https://twitter.com/KimKardashian/status/887881898805952514 And she went and took the test, BUT SHE DIDN'T SCORE AS A KIM!! SHE SCORED AS A CHRISSY! See below. https://twitter.com/KimKardashian/status/887882791488061441 So, this test purports to assess one's Kim Kardashian-West-ness or one's Chrissy Teigan-ness. And it failed to measure what it claimed to measure as Kim didn't score as a Kim. So, not a valid measure. No word on how Chrissy scored. And if you are in you teach people in their 30s, you could always use this example of the time Garbage's Shirley Manson...