The following email recently came across the Society for the Teaching of Psychology listserv from Robert Calin-Jageman (email@example.com).
"Is anyone out there incorporating the "New Statistics" (estimation, confidence intervals, meta-analysis) into their stats/methods sequence?
I'm working with Geoff Cumming on putting together an APS 2017 symposium proposal on teaching the New Statistics. We'd love to hear back from anyone who has already started or is about to. Specifically, we'd love to:
* Collect resources you'd be willing to share (syllabi, assignments, etc.)
* Collect narratives of your experience (the good, the bad, the unexpected)
* Know what tips/suggestions you might have for others embarking on the transition
We'll use responses to help shape our symposium proposal (and if you're interested in possibly joining, let us know).
In addition, we're curating resources, tips, on a "Getting started teaching the New Statistics" page on the OSF : https://osf.io/muy6u/"
I'll start by sharing to examples I have successfully used in class and have previously blogged about. Here is a post about a Facebook research study (Kramer, Guillory, & Hancock, 2014) that demonstrates how large sample sizes lead to statistical significance but very small effect sizes. This study also demonstrates how to mislead with graphs and the debate of whether or not Terms of Service agreements are the same thing as informed consent.
And I use this Colbert interview with Daryl Bem in which Bem is basically arguing for p-values without ever saying "p-values", and Colbert is arguing for effect size/clinical significance without ever saying those words. I follow up this video by sharing a table from the much-debated Bem, 2014 JPSP article that displays, again, small p-values and large effect sizes. NOTE: This interview is about the Bem, 2014 research that used erotic imagery as stimuli, so the tone of the interview might be a little racy for inclass use at some universities/high school statistics classes.
Finally, I use Kristopher Magnussen's website to illustrate a quite a few statistical principles, including Cohen's d.
So, I am sharing it here to reach out to all of you statistics instructors to see 1) if you are interested in sharing your ideas for the APS symposium/OSF resource, 2) would like to look out for the APS symposium if you are attending next year, 3) alert you to the great OSF resource listed above, and in the spirit of the holiday season, 4) share, share, share.