Monday, November 28, 2016

Teaching the "new statistics": A call for materials (and sharing said materials!)

This blog is usually dedicated to sharing ideas for teaching statistics. And I will share some ideas for teaching. But I'm also asking you to share YOUR ideas for teaching statistics. Specifically, your ideas for teaching the new statistics: effect size, confidence intervals, etc.

The following email recently came across the Society for the Teaching of Psychology listserv from Robert Calin-Jageman (

"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 :"

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.  

1 comment:

  1. Thanks for this. It's helpful.

    I teach meta-analysis/effect sizes in an MA stats course for Child & Youth Care students (CYC is a Canadian thing). I've learned the best way to teach it is not to teach: The students pick a published meta-analysis, and they duplicate the analysis. I provide resources and problem solving help, but they learn faster and with more depth if they figure it out on their own. They help each other with the comprehension and apply it to their own individual work.