NPR did a series of stories exposing research that the U.S. government conducted during WWII. This research exposed American soldiers to mustard gas for research purposes. In some instances, the government targeted soldiers of color, believing that they had tougher/different skin that would make them more resistant to this form of chemical warfare. Here is the  whole series of stories  (from the  original research, exposed via Freedom of Information Act , to  NPR working to find the effected veterans ). None of the soldiers ever received any special dispensation or medical care due to their involvement. Participants were not given the choice to discontinue participation without prejudice, as recalled below by one of the surviving veterans: "We weren't told what it was," says Charlie Cavell, who was 19 when he volunteered for the program in exchange for two weeks' vacation. "Until we actually got into the process of being in that room and realized, wait a m...

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 ...

I often share news stories that illustrate easy-to-follow, engaging research that appeals to undergraduates. For the first time, I'm also providing a mini data set that 1) mimics the original findings and 2) provides an example of ANOVA. This story by Patty Neighmond , reporting for NPR, describes a  study  investigating the role of music in pain reduction. The study used three groups of kids, all recovering from surgery. The kids either 1) listened to music, 2) listened to an audio books, or 3) sat with noise-cancelling ear phones for 30 minutes. The researchers found that kids in both the music and audio book experienced pain reduction levels comparable to over-the-counter pain medication while the control group enjoyed no such benefits. And the research used the 10-point FACES scale, allowing for a side discussion about how we collect data from humans who don't have the best vocabularies or limited communication skills. This study can also be used as a way t...

For those who teach statistics, research methods, and psychology major advisers. Some of these have been posted before. Some of these have not. I created all of them except for the first one. Additionally, I created a bunch of Psychology Advising memes as I am currently editing the "Advising" portion of my rank and tenure application.

Once again, Kristopher Magnusson has combined is computer programming and statistical knowledge to help illustrate statistical concepts . His latest  interactive tool allows students to view the t-curve for different degrees for freedom. Additionally, students can view error rates associated with different degrees of freedom. Note that the critical region is one-tailed with alpha set at .05. If you cursor around the critical region, you can set the alpha to .025 to better illustrate a two-tailed test (in terms of the critical region at which we declare significance).  Error rates when n < 30 Error rates when n > 30 This isn't the first time Kristopher's interactive tools have been featured on this blog! He has also created websites dedicated to explaining effect size , correlation , and other statistical concepts .

I think that it is so, so important to introduce statistics students to the big picture of how data is used in their every day lives. Even with all of the material that we are charged with covering in introduction to statistics, I think it is still important to touch on topics like Big Data and Data Mining in order to emphasize to our students how ubiquitous statistics are in our lives.  In my honors section, I assign multiple readings (news stories, TED talks, NPR stories) prior to a day of discussion devoted to this topic. In my non-honors sections of statistics and my online sections, I've used electronic discussion boards to introduce the topic via news stories. I also have a manuscript in press that describes a way to introduce very basic data mining techniques in the Introduction to Statistics classroom. That's why I think this NPR news story is worth sharing. Shahani describes and provides data (from Pew) to argue that Americans are worried about the security of...

The original idea for using this article this way comes from Dr. Susan Nolan 's presentation at NITOP 2015, entitled " Thinking Like a Scientist: Critical Thinking in Introductory Psychology."  I think that Dr. Nolan's idea is worth sharing, and I'll reflect a bit on how I've used this resource in the classroom. (For more good ideas from Dr. Nolan, check out her books, Psychology , Statistics for the Behavioral Sciences , and The Horse that Won't Go Away (about critical thinking)). Last summer, the National Academy of Sciences Proceedings published an article entitled "Experimental evidence of massive-scale emotional contagion through social networks ." The gist: Facebook manipulated participants' Newsfeeds to increase the number of positive or negative status updates that each participant viewed. The researchers subsequently measured the number of positive and negative words that the participants used in their own status updates. They fou...

Jethro Waters, Dan Peterson, Ph.D., Laurie McCollough, and Luke Norton made a pair of animated videos ( 1 , 2 ) that explain why correlation does not equal causation and how we can perform lab research in order to determine if causal relationships exist. I like them a bunch. Specific points worth liking: -Illustrations of scatter plots for significant and non-significant relationships. Data does not support the old wive's tale that everyone goes a little crazy during full moons. -Explains the Third Variable problem. Simple, pretty illustration of the perennial correlation example of ice cream sales (X):death by drowning (Y) relationship, and the third variable, hot weather (Z) that drives the relationship. -In addition to discussing correlation =/= causation, the video makes suggestions for studying a correlational relationship via more rigorous research methods (here violent video games:violent behavior). Video games (X) influence aggression (Y) via the moderato...

Back in the day, I remember having to complete an online research ethics course in order to serve as an undergraduate research assistant at Penn State. I think that such training could be used as an exercise/assessment in a research methods class or an advanced statistics class. NOTE: These examples are sponsored by the American agencies and, thus, teach participants about American laws and rules. If you have information about similar training in other countries (or other free options for American researchers), please email me and I will add the link. Online Research Ethics Course from the U.S. Health and Human Service's Office of Research Integrity. Features: Six different learning modules, each with a quiz and certificate of completion. These sections include separate quizzes on the treatment of human and animal test subjects. Other portions also address ethical relationships between PIs and RAs and broader issues of professional responsibility when reporting results. ...

It's coming, guys. But let's get ahead of it. I thought I would re-share some resources that you may want to consider working into your curriculum this year. I picked out a few lessons and ideas that also require a bit of forethought and planning, especially if they become assessment measures for your class. Center for Open Science workshops: As previously discussed on this blog , COS offers f ree consultation  (face-to-face or online) to faculty and students in order to teach us about the open framework for science. They provide guidance about more more traditional statistical issues, like power calculations and conducting meta-analysis in addition to lessons tailored to introducing researchers to the COS framework. Take your students to an athletic event , talk about statistics and sports : I took my students to a baseball game and worked some statsy magic. You can do it, too. If not a trip to the ballpark, an on-campus or televised athletic event will w...

Ben Blatt of Slate mined through Center for Disease control data in order to provide us with 13 different maps of the United States and mortality information for each state . Below, information on disproportionately high cases of death in each state. While the maps are morbid and interesting, the story behind the maps ( read the story here about how data can be easily misrepresented by maps ) make this a good example of how easily data can be distorted. The story along with the maps unveils several issues that statisticians/researchers must consider when they are presenting descriptive statistics. In this instance, Blatt had to sort through the data to eliminate the most common causes of death (heart disease, cancer, etc.) in order to uncover unique data for each state. Relatedly, he highlights the fact that "disproportionately" does not mean "most": "But this map—like many maps which purport to show attributes meant to be “distinct” or “disproporti...

Pew recently revisited the question of how survey modality can influence survey responses.  In particular, this survey used both web and telephone based surveys to ask participants about their attitudes towards politicians, perceptions of discrimination, and their satisfaction with life. As summarized in the article, the big differences are: "1)  People expressed more negative views of politicians in Web surveys than in phone surveys."  "2)  People who took phone surveys were more likely than those who took Web surveys to say that certain groups of people – such as gays and lesbians, Hispanics, and blacks – faced “a lot” of discrimination ."  "3)  People were more likely to say they are happy with their family and social life when asked by a person over the phone than when answering questions on the Web ."     The social psychologist in me likes this as an example of the Social Desirability Bias. When spea...

I take credit for none of these. A few have been posted here before. by Rayomond Biesinger, http://fifteen.ca/ Creator unknown, usually attributed to clipart? http://www.sciencemag.org/content/331/6018.cover-expansion https://www.flickr.com/photos/lendingmemo/ https://lovestats.wordpress.com/2014/11/10/why-do-kids-and-you-need-to-learn-statistics-mrx/ http://memecollection.net/dmx-statistics/ 9/23/15 Psychometrics: Interval scale with proper anchors 2/9/16 4/19/16 4/28/16 "Symbols that math urgently needs to adopt" https://mathwithbaddrawings.com/2016/04/27/symbols-that-math-urgently-needs-to-adopt/ http://www.mrlovenstein.com/ http://www.smbc-comics.com/ 9/8/16 2/9/2107 https://hbr.org/2017/02/if-you-want-to-motivate-employees-stop-trusting-your-instincts https://www.theguardian.com/politics/2017/jan/19/crisis-of-statistics-big-data-democracy?CMP=share_btn_tw 2/13/17 ...