I teach many, many statistics classes. In addition to the core topics typically covered in Introductory Statistics, I think covering real-life controversies involving statistics is vital. Usually, these are stories of large organizations that attempted to bias/PR attack/skew/p-hack/cherry-pick data to serve their own purposes.  I believe that these examples serve to show why data literacy is so critical because data is used in so many fields, AND our students must prepare themselves to evaluate data-based claims throughout their lives. I put out a call on Twitter , and my friends there helped me generate a great list of such controversies. I put this list into a spreadsheet with links to primers on each topic. This isn't an in-depth study of any of these topics, but the links should get you going in the right direction if you would like to use them in class. I hope this helps my fellow stats teachers integrate more applied examples into their classes. If you h...

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...

This news story demonstrates that research methods are both federally monitored and that best practices can change over time. For a long time, women were not used in large scale pharmaceutical trials. Why did they omit women? They didn't want to accidentally exposed pregnant women to new drugs and because of fears that fluctuations in females hormones over the course of a month would affect research results. Which always makes me think of this scene from Anchorman: But I digress. This has been corrected for and female participants are being included in clinical trials. But many of the animal trials that occur prior to human trials still use mostly male animals. And, again, policies have changed to correct for this. This NPR story details the whole history of this sex bias in research. Part of why this bias has been so detrimental to women is because women report more side effects to drugs than do men. So, by catching such gender differences earlier with animal models, the...