Okay. I know there are so many COVID examples out there, but this one is maybe a tiny bit amusing (it involves Berlin dance clubs). It also demonstrates a within-subject research design and ecological validity. It is also a very tiny example that is easy to understand and doesn't require students to understand any psychological theories. Yes, many of you are psychologists teaching statistics, but I think it is vital that we use various examples to ensure that at least one of them will stick for every student. Emma Hurt/NPR Anyway. Berlin has a famous dance club culture , which has been under tremendous financial strain due to COVID-19. Since winter is coming and outdoor options will no longer be possible, the government has sponsored a pilot project to study whether or not clubs can be opened safely if everyone at the club has tested negative for COVID-19. NPR reported on this applied, within-subject design study  (a three-minute-long news story you could use in class): In addition...

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 am absolutely NOT above pandering to undergraduates. For example, I use beer-related examples to illustrate t-test s,   correlation/regression , curvilinear relationships , and data mining/re-purposing . Here is some more. This data was collected to estimate how much more participants would pay for their beer if their beer was created in an environmentally sustainable manner. The answer? $1.30/six pack more. And 59% of respondents said that they would pay more for sustainable beer. NPR talked about it , as well as ways that breweries are going green. Here is a link to the original research . How to use in class: 1) The original research is shared via an open source journal . So, an opportunity to talk about open source research journals. 2) They data was collected via mTurk, another ancillary topics to discuss with your budding research methodologists. 3) The authors of the original study shared their beer survey data ! Analyze to your heart's content. 4) How c...

As described here, legislatures in Puerto Rico attempted to take independent authority away from the Puetero Rican Institute of Statistics (PRIS), a governmental watch dog in charge of double checking statistics and research methods used by the government . This decision was made in order to streamline government, which is understandable. But it was also problematic because watchdogs need independence in order to have the power and safety to say unpopular things. Anyway, the legislatures ended up NOT streamlining PRIS's and taking away its authority, in part due to an outcry from other scientific agencies. How to use in class: -Statistics in real life, informing decisions, informing funding, being controversial. -Why do organizations like American Statistical Association and American Association for the Advancement of Science exist? Well, for a lot of reasons, one of which is t o publicly protests moves like the one PR tried to execute. -Statisticians and scientists aren...

https://pudding.cool/2018/01/chyrons/ This example doesn't demonstrate a specific statistical test. Instead, it demonstrate how data can be used to answer a hotly contested question: Are certain media outlets biased? How can we answer this? Charlie Smart, working for The Pudding, addressed this question via content analysis. Here is how he did it: And here are some of their findings: Yes, Fox News was talking about the Clintons a lot. While over at MSNBC, they discussed the investigation into Russia and the 2016 elections ore frequently. While kneeling during the anthem was featured on all networks, it was featured most frequently on Fox And context matters. What words are associated with "dossier"? How do the different networks contextualize President Trump's tweets? Another reason I like this example: It points out the trends for the three big networks. So, we aren't a bunch of Marxist professors ragging on FOX, and we ar...

Anna Scott, reporting for NPR, described changes to the homeless census in LA . It applies to stats/RM because an improvement in survey methodology lead to a big change in the city's estimation of number of homeless young adults. I also think this is also a good piece for teaching because the story keeps coming back to Japheth Greg Dyer, a homeless college student who aged out of the foster care and was sort of tossed into the world on his own. Straight from NPR: Homelessness hasn't necessarily increased dramatically. Instead, these findings seem to indicate that they finally have a reliable way to count young adult homelessness due to a better understanding of young adults. The dramatic increase is methodological.

My son, Artie, resting in the NICU When my second son was born via emergency c-section, he spent a week in the NICU out of an abundance of caution. It wasn't fun, but Artie pulled through just fine. He is a fat, happy four-month-old now. While we were there, I found out that many of the other NICU babies there were suffering from neonatal abstinence syndrome (NAS). They were born addicted to drugs. And those poor babies howled for hours as they were being weaned off of drugs and helped by staff. NPR's All Things Considered recently did a series about national efforts to help end NAS. Two of the segments from this series are possible learning moments for statistics and RM classes. One discusses efforts to use proper research methodology to create better treatment recommendations for NAS babies . The second discusses governmental efforts to use systematic data collection to better track NAS babies and get to the root of the problem . 1. Using clinical research to bette...

EDIT: All of this content appears to have been removed from NFL.com. If anyone has any luck finding it, please email me at hartnett004@gannon.edu The NFL and the statistics folks over at Freakonomics got together and made some...learning modules? Let's call them learning modules. They are interactive websites that teach users about very specific questions related to football (like home field advantage , instances when football player statistics don't tell the whole story about a player/team , whether or not firing a head coach improves a failing team , the effects of player injury on team success , etc.) and then answer these questions via statistics. Most of the modules include interactive tables, data, and videos (featuring the authors of Freakanomics) in order to delve into the issue at hand. For example: The Home Field Advantage : This module features a video, as well as a interesting interactive map that illustrates data about the exact sleep lost experienced by ...

There are a number of TED talks that apply to research methods and statistics classes. First, there is this TED playlist entitled The Dark Side of Data . This one may not be applicable to a basic stats class but does address broader ethical issues of big data, widespread data collection, and data mining. These videos are also a good way of conveying how data collection (and, by extension, statistics) are a routine and invisible part of everyday life. This talk by Peter Donnelly discusses the use of statistics in court cases, and the importance of explaining statistics in a manner that laypeople can understand. I like this one as I teach my students how to create APA results sections for all of their statistical analyses. This video helps to explain WHY we need to learn to report statistics, not just perform statistics. Hans Rosling has a number of talks (and he has been mentioned previously on this blog, but bears being mentioned again). He is a physician and conveys his passion...

Kamenetz (reporting for NPR) talks about her book , Test , which is about the extensive use of standardized testing in our schools. Largely, this is a story about the impact these tests have had on how teachers instruct K-12 education in the US. However, a portion of the story discusses alternatives to annual testing of every student. Alternatives include using sampling to assess a school as well as numerous alternate testing methods (stealth testing, assessing child emotional well-being, portfolios, etc.). Additionally, this story touches on some of the implications of living in a Big Data society and what it is doing to our schools. I think this would be a great conversation starter for a research methods or psychometric course (especially if you are teaching such a class for a School of Education). What are we trying to assess: Individual students or teachers or schools? What are the benefits and short comings of these different kinds of assessments? Can you students come up with...

This Scientific American podcast by Diane Fine Maron describes how the Chicago Department of Public Health (CDPH) used Twitter data to shut down restaurants with health code violations. Essentially, the CDPH monitored Tweets in Chicago, searching for the words "food poisoning". When such a tweet was identified, an official at CDPH messaged the Twitterer in question with a link to an official complain form website. The results of this program? "During a 10-month stretch last year, staff members at the health agency responded to 270 tweets about “food poisoning.” Based on those tweets, 193 complaints were filed and 133 restaurants in the city were inspected. Twenty-one were closed down and another 33 were forced to fix health violations. That’s according to a study in the journal  Morbidity and Mortality Weekly Report.  [Jenine K. Harris et al,  Health Department Use of Social Media to Identify Foodborne Illness — Chicago, Illinois, 2013–2014 ]" I think this is ...

This radio story  by Mara Liasson (reporting for NPR) discusses the surprising primary loss of former Republican House Majority Leader Eric Cantor. It was surprising because internal polling conducted by Cantor's team gave him an easy win, but he lost out to a Tea Party favorite, David Brat. The story goes on to describe why it is becoming increasingly difficult to conduct accurate voter polling via telephone and the internet. Some specific points from this story that teach students about sampling techniques: 1) Sample versus population: One limitation of polling data is the fact that many telephone call-based sampling techniques include landlines and ignore the growing population of people who only have cell phones. 2) Response rates for political polling are on a decline, making the validity of the available sample shrink. 3) Robocalls, while less expensive, have no way of validating that an actual registered voter is responding to the questions. Additionally, restrictio...

I am busy prepping my statistics class for the fall (as well as doing a bunch of stuff that I should have done in June, but I digress). Most of my students are required to take statistics and are afraid of mathematics so I'm going to try to convince them to embrace statistics by showing them that more and more non-statsy jobs require data collection, data analysis, data driven decisions, program assessment, etc..  I find that my students are increasingly aware of the current job market as well as their student loan debt. As such, I think that students are receptive to arguments that  explain  how even a little bit of statistical knowledge can make them more attractive to potential employers. Here are some resources I have found to do just that.  This article by Susan Adams for Forbes lists the top ten skills employers are looking for in employees. Included in the top ten: "2. Ability to make decisions and solve problems 5. Ability to obtain and ...

This story details the application of American election polling techniques to Afghanistan's fledgling democracy. Essentially, international groups are attempting to poll Afghans prior to their April 2014 presidential elections as to combat voter fraud and raise awareness about the election. However, how do researchers go about collecting data in a country where few people have telephones, many people are illiterate, and just about everyone is weary about strangers approaching them and asking them sensitive questions about their political opinions? The story also touches on issues of social desirability as well as the decisions  a researcher makes regarding the kinds of response options to use in survey research. I think that this would be a good story to share with a cranky undergraduate research methods class that thinks that collecting data from the undergraduate convenience sample is really, really hard. Less snarkily, this may be useful when teaching multiculturalism or ...

I am teaching positive psychology for the first time this semester. One way to quickly teach students that this isn't just Happy Psych. 101 is to show them convincing data collected by an international organization (here, the United Nations) that demonstrates the link between positive psychology and the well-being of nations. This data isn't just for a positive psychology class: You could also use it more broadly to demonstrate how research methods have to be adjusted when data is collected internationally (see item 4) and as examples of different kinds of data analysis (as described under item 1). 1) Report on international happiness data from the United Nations . If you look through the data collected, there is a survival analysis related to longevity and affect on page 66. A graphic on page 21 describes factors that account for global variance in happiness levels across countries. There is also a lot of data about mental health care spending in different nations. 2 ...

The Travel Security Agency implemented SPOT training in order to teach air port security employees how to spot problematic and potentially dangerous individuals via behavioral cues. This intervention has cost the U.S. government $1 billion+. It doesn't seem to work. By discussing this with your class, you can discuss the importance of program evaluations as well as validity and reliability. The actual government issued report goes into great detail about how the program evaluation data was collected to demonstrate that SPOT isn't working. The findings (especially the table and figure below) do a nice job of demonstrating the lack of reliability and the lack of validity. This whole story also implicitly demonstrates that the federal government is hiring statisticians with strong research methods backgrounds to conduct program evaluations (= jobs for students). Here is a summary of the report from the Washington Post. Here is a short summary and video about the report from ...

I like the following examples because they are accessible, potentially life-saving, and demonstrate statistics that disprove convention (and saves lives!), and provide a good argument for program evaluation. For decades, prevailing wisdom stated that we should put babies to sleep on their stomachs so that they wouldn't choke on their own spit-up in their sleep. Then, lo-and-behold, data suggested that putting babies to sleep on their back reduced deaths due to Sudden Infant Death Syndrome (SIDS). BY HALF. Data disproved convention AND improved public health dramatically and cheaply as the American Academy of Pediatrics rolled out the Back To Sleep campaign to inform parents about this research and best practices for bedtime. Now, the law of unintended consequences: Wee little babies are developing flat heads! My own son did (he is the cutie in the helmet), and required a helmet and physical therapy to correct the condition. More on the flat head (technical name: plagioenc...

According to this data from the National Weather Service , lightning is a big, man-hating jerk!   From NWS/NOAA   And Might Thor lives to be your weekend's buzz kill! Or not. Play "Spot the Third Variable" with your students.

I guess "The Longevity Game" sounds better than The Death Calculator. Which is what Northwestern Mutual has created and shared with us. Essentially, you answer questions about yourself (weight, exercise, stress management, driving habits, drug and alcohol habits, etc.) and the Game will give you an estimation for how long you should live based on the data you provide. The Longevity Game, from Northwestern Mutual I use this in class to demonstrate how data and statistics influence certain aspects of our lives (like whether or not an insurer is willing to provide us with insurance coverage). This can also be used to introduce multiple regression, since multiple factors are taken into account when predicting the outcome measure of life expectancy. I also make sure to emphasize to my students that this calculator was created by an insurance company that was founded in 1857 and that this calculator isn't just some random interwebz quiz. Warning: I wouldn't ask...

University of Cambridge's Psychometric Center has used statistics to make make personality predictions based upon an individual's Facebook "likes" . For instance, your likes can be used to create your Big Five personality trait profile. Your students can have their data FB "likes" analyzed at YouAreWhatYouLike.com  as to determine their Big Five traits. After your students complete the FB version of the scale, you could have your students complete a more traditional paper and pencil version of the inventory and discuss differences/similarities/concurrent validity between the two measures. Below, I've included a screen grab of my FB-derived Big Five rating from YouAreWhatYouLike.com. Note: Yes, that is how I score on more traditional versions of the same scale. Generated at YouAreWhatYouLike.com In addition to Big Five prediction, the researchers also used the "like" data to make predictions of other qualities, like sexual orientatio...