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...

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? 

This NPR story discusses research  detective work published JAMA . The JAMA article looked at a very influential NEJM review article that investigated the link between diet and Coronary Heart Disease. Specifically, whether sugar or fat contribute more to CHD. The article, written by Harvard researchers decades ago, pinned CHD on fatty diets. But the researchers took money from Big Sugar (which sounds like...a drag queen or CB handle) and communicated with Big Sugar while writing the review article. This piece discusses how conflict of interest shaped food research and our beliefs about the causes of CHD for decades. And how conflict of interest and institutional/journal prestige shaped this narrative. It also touches on how industry, namely sugar interests, discounted research that finds a sugar:CHD link while promoting and funding research that finds a fat:CHD link. How to use in a Research Methods class: -Conflict of interest. The funding received by the researchers from th...

This article from The Washington Post summarizes research published in the Journal of the American Medical Association . Both are simple, short articles that show how you can use regression to make an argument. Here, the authors use regression to demonstrate the paucity of funding and publications for research studying gun-related deaths. A regression line was generated to predict how much money was spent studying common causes of death in the US. Visually, we can see that deaths by firearms aren't receiving funding proportional to the number of deaths they cause. See the graph below. How to use in class: 1) How is funding meted out by our government to better understand the problems that plague our country? Well, it isn't being given to researchers studying gun violence because of the Dickey Amendment . I grew up in a very hunting friendly/gun-friendly part of Pennsylvania. I've been to the shooting range. And it upsets me that we can't better understand and stu...

This example from Retraction Watch illustrates how NOT to do research. It is a study that was accepted and retracted from Frontiers in Public Health. It purported to find a link between childhood vaccination and a variety of childhood illnesses. This would be a good case study for Research Methods. In particular, this example illustrates: 1) Retraction of scientific studies 2) The problems with self-report surveys 3) Sampling and trying to generalized from biased samples 4) What constitutes a small sample size depending on the research you are conducting 5) Conflict of interest This study, since retracted, studied unvaccinated, partially vaccinated, and fully vaccinated children. And the study found " Vaccinated children were significantly less likely than the unvaccinated to have been diagnosed with chickenpox and pertussis, but significantly more likely to have been diagnosed with pneumonia, otitis media, allergies and NDDs (defined as Autism Spectrum Disorder, Attenti...

Refutation to Anti-vaccination Memes  came up with this excellent illustration to explain why anti-vaxxers shouldn't claim a "win" just because more vaccinated people than unvaccinated people get sick during an outbreak. This example has a bit more credence if paired with actual immunization rate/infection rate data. For instance, in a case when an outbreak has occurred, and most infected are immunized, but there were still some un-immunized individuals. To further this case, yes, most people in America are immunized . However, here  is an example of an outbreak that has been linked to un-vaccinated folks. How to use it in class: -Base rate fallacy (which DOES matter when making an argument with descriptive stats!) -Relative v. absolute risk. -Making sense of and contextualizing descriptive statistics.

Here is another example of why representative sampling MUST include women. For years and years, car crash test dummies for adults were all based upon the 50th percentile male. As such, even in vehicles with high safety ratings, women still have higher rates of certain injuries (head, neck, pelvis) than men. In fact, the article cites research that found that belted female car occupants in accidents have a 47% higher chance of suffering a serious injury and a 71% higher chance of suffering a moderate injury compared to men in a car. http://leevinsel.com/blog/2013/12/30/why-carmakers-always-insisted-on-male-crash-test-dummies I wrote a previous blog post about this video that outlines how using only  male rats for pharmaceutical research lead to problems with disproportionately high numbers of side effects in female humans . And this NPR story details changes to federal rules in order to correct this issue with animal testing. How to use in class: -Inappropriate sampling i...

The folks at Wall Street Journal took CDC disease data (by state, by year, courtesy of Project Tycho ) as well as information on when various vaccines were introduced to the public. And the data tells a compelling story about the importance of vaccinations. Below, the story of measles. How to use in class: -Using archival data to educate and make a point (here, vaccine efficacy) -Visualizing many data points (infections x state x year) effectively -Interactive: You can cursor over any cube to see the related data. Below, I've highlighted Pennsylvania data from 1957. -Since you can cursor over any data point to see the data, you can ask your students to pull data for use in class. -The present data were drawn from Project Tycho , a University of Pittsburgh initiative to better share public health data. This resource may be useful for your classes as well. -This data is good for Stats class, as well as Developmental, Health, Public Health, etc.

Our World in Data is an impressive, creative-commons licensed site managed by Max Roser . And it lives up to its name. The website provides all kinds of international data, divided by country, topic (population, health, food, growth & inequality, work, and life, etc.), and, when available, year. It contains its own proprietary data visualizations, which typically feature international data for a topic. You can customize these visualizations by nation. You can also DOWNLOAD THE DATA that has been visualized for use in the classroom. Much of the data can be visualized as a map and progress, year by year, through the data, like this data on international human rights. https://ourworldindata.org/human-rights/  https://ourworldindata.org/human-rights/ There are also plenty of topics of interest to psychologists who aren't teaching statistics. For example, international data on suicide: Data for psychology courses...https://ourworldindata.org/suicide/ Work...

Factorial ANOVA example ahead! With a lovely interaction. And I have a year old and a 4.5 year old and they are sickly daycare kids, so this example really spoke to me. NPR did a story about a recent publication that studied how we administer medicine to our kids and provides evidence for a few things I've suspected: Measuring cups for kid medicine are a disaster AND syringes allow for more accurate dosing, especially if the dose is small. The researchers wanted to know if parents properly dosed liquid medicine for their kids. The researchers used a 3 (dosage, 2.5, 5.0, 7.5 ml) x 3 (modality: small syringe, big syringe, medicine cup) design. They didn't use factorial ANOVA in their analysis, this example can still be used to conceptually explain factorial ANOVA. Their findings: How to use in class: -An easy-to-follow conceptual example of factorial ANOVA (again, they didn't use that analysis in the original paper, but the table above illustrates factorial ANO...

In honor of the New Year, a post about health.  A team of researchers from Harvard made a brief video that describes their recent publication. The video includes discussion about their hypothesis generation, methodology, and research findings.  Their research question: Does the game Pokemon Go actually improve the health of users? How to use this video in your class: -This is an easily understood research project to share with your RM students. It also goes into detail about the statistics used for analysis. -And the researchers, from fancy-pants Harvard, aren't afraid of being a bit silly and having fun as researchers. As demonstrated by the below images from the video: This guy. Seriously. I hope to some day love my data as much as he loves his data. And they made graphs using Pokemon balls -How do we get our research ideas? Sometimes, from observations about every day living. This research was inspired by the Pokemon Go phenomena. I try to ...

Property of  @JenSacco54 http://www.huffingtonpost.com/entry/mariah-carey-christmas_us_561f989be4b0c5a1ce621a69 A wintery example of why range is a crap measure of variability http://qz.com/859303/americas-most-common-christmas-related-injuries-in-charts/

Fivethirtyeight provides lots of beautiful pictures of spurious correlations found by their own in-house study. At the heart of this article are the limitations of a major tool use in nutritional research, the Food Frequency Questionnaire (FFQ). The author does a mini-study, enlisting the help of several co-workers and fivethirtyeight.com readers. They track track their own food for a week and reflect on how difficult it is to properly estimate and recall food (perhaps a mini-experiment you could do with your own students?). And she shares the spurious correlations she found in her own mini-research: Aschwanden also discusses how much noise and lack of consensus their is in real, published nutritional research (a good argument for why we need replication!):  http://fivethirtyeight.com/features/you-cant-trust-what-you-read-about-nutrition/ How to use in class: -Short comings of survey research, especially survey research that relies on accurate memories -...

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:

This NPR story is a summary of the decisively titled " The Mass Production of Redundant, Misleading, and Conflicted Systematic Reviews and Meta-analyses " authored by Dr. John Ioannidis. The NPR story provides a very brief explanation of meta-analysis and systematic reviews. It explains that they were originally used as a way to make sense of many conflicting research findings coming from a variety of different researchers. But these very influential publications are now being sponsored and possibly influenced by Big Pharma. This example explains conflicts of interest and how they can influence research outcomes. In addition to financial relationships, the author also cites ideological allegiances as a source of bias in meta-analysis. In addition to Dr. Ioannidis, Dr. Peter Kramer was interviewed. He is a psychiatrist who defends the efficacy of antidepressants. He suggests that researchers who believe that placebos are just as effective as anti-depressants tend to analy...

Two scientists, Lazris and Rifkin, want to better illustrate the risks and benefits associated with preventative medicine. They do so by asking people to imagine theaters filled with 1,000 people, and describing the costs and benefits for different preventative procedures by discussing how many people in the theater will be saved or perish based on current efficacy data. One such video can be viewed here and illustrates the absolute and relative risks associated with mammography. They are attempting to demystify statistics and better explain the risks and benefits by showing an animated theater filled with 1,000 women, and showing how many women actually have their lives saved by mammograms (see screen shot below)... ...as well as the number of women who received false positives over the course of a life time... A screen shot of the video, which is trying a new way to illustrate risk. ...the video also illustrates how a "20% reduction in breast cancer deaths" ca...

Data USA draws upon various federal data sources in order to generate visualizations about cities and occupations in the US. And it provides lots of good examples of simple, descriptive statistics and data visualizations. This website is highly interactive and you can query information about any municipality in the US. This creates relevant, customized examples for your class. You can present examples of descriptive statistics using the town or city in which your college/university/high school is located or you could encourage students to look up their own hometowns. Data provided includes job trends, crime, health care, commuting times, car ownership rates...in short, all sorts of data. Below I have included some screen shots for data about Erie, PA, home of Gannon University: The background photo here is from the Presque Isle, a very popular state park in Erie, PA. And, look, medians!

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.

Good data should inform our decisions. Even a really stressful decision. This site demonstrates this beautifully by providing UK pediatric hospital survival rates to aid the parents of children undergoing heart surgery. The information is translated for laypeople. They present statistical ideas that you and your students have heard of but without a lot of statistical jargon. The data is also explained very clearly. For example, they  present detailed hospital survival rates , which include survival ranges: So, it contains data from a given period. It includes the actual mortality rate and a range likely to have a valid mortality rate. So, essentially, they are confidence intervals but not precisely confidence intervals. In addition to this more traditional presentation of the data, the survival ranges are explained in greater detail in a video . I think this video is helpful because it describes the distribution of the sample mean and how to use them to estimate ac...

Organizations have frequently tried to shut down/manipulate data for their own ends. Big tobacco and lung cancer and addiction research . The National Football League and Chronic Traumatic Encephaly . And for the last 20 years, the National Rifle Association has successfully blocked funding for research investigating public safety and gun ownership. Essentially, the NRA has concentrated on eliminating funding at the CDC for research related to a better understanding of how guns hurt people. It started in 1996 with the Dickey Amendment and no one has been willing to fight to bring back funding. The APA wrote a piece on this in 2013 that summarizes the issue. In the wake of the shooting in Orlando, NPR did a story explaining how the American Medical Association is trying to change the rules governing gun research  and  the L.A. times published this column . I think this precedence is unfortunate from both sides of the gun debate. I grew up in rural Pennsylvania. I've...