This is an excellent video for introducing t -tests AND finally getting the story straight regarding William Gossett, Guinness Brewery, and why Gossett published under the famous Student pseudonym. What did I learn? Apparently, Gossett DID have Guinness' blessings to publish. Also, this story demonstrates statisticians working in Quality Assurance as the original t-tests were designed to determine the consistency in the hops used in the brewing process. Those jobs are still available in industry today. Credit goes to the RStats Institute at Missouri State University.  This group has created many other tutorial videos for statistics as well.

Jennifer Raff  is a geneticist, professor, and enthusiastic blogger . She  created a helpful guide for how non-scientists (like our students) can best approach and make sense of research articles. The original article is very detailed and explains how to make sense of experts. Personally, I appreciate that this guide is born out of trying to debate non-scientists about research. She wants everyone to benefit from science and make informed decisions based on research. I think that is great. I think this would be an excellent way to introduce your undergraduates to research articles in the classroom. I especially appreciated this summary of her steps (see below). This could be turned into a worksheet with ease. Note: I still think your students should chew on the full article before they are ready to answer these eleven questions. http://blogs.lse.ac.uk/impactofsocialsciences/2016/05/09/how-to-read-and-understand-a-scientific-paper-a-guide-for-non-scientists/#author ...

New York Magazine's  The Science of Us made a brief, funny video that investigates the long running issue of the dangers of double dipping.  It is based on a Scientific America report of an actual published research article  about double dipping. Yes, it includes the Seinfeld clip about George double dipping. The video provides a brief example of how to go about testing a research hypothesis by operationalizing a hypothesis, collecting, and analyzing data. Here, the abstract question is about how dirty it is to double dip. And they operationalized this question: Research design: The researchers used a design that, conceptually, demonstrates ANOVA logic (the original article contains an ANOVA, the video itself makes no mention of ANOVA). The factor is "Dips" and there are three levels of the factor: Before they double dipped, they took a base-line bacterial reading of each dip. Good science, that. They display the findings in table form (aga...

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.

The Southern Poverty Law Center has used mapping software in order to illustrate the location of different hate groups in the US. How to use in class: I think this demonstrates how good old descriptive data collection plays a valuable roll in law enforcement, social justice, etc. I think this demonstrates why well-visualized data may be a more compelling way of sharing information than data in tables. Another way to use this is for your students to create a methods section based upon the data collection information provided on the website: You can make the data more personalized for your class by digging down to state-wide data. In addition to the maps, the website includes various other descriptive data quantifying different hate groups in the US. I used this in class along with  other examples of how data can be mixed with maps in order to provide information on regions/states. This could also be used in a Social Psychology class in order to illustrat...

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.