This last weekend I helped Danny Kaplan and Kathryn Kozak (Coconino Community College) put on a StatPREP workshop. We were also joined by Amelia McNamara (Smith College) and Joe Roith (St. Catherine’s University). The idea behind StatPREP is to work directly with college-level instructors, through online and in community-based workshops, to develop the understanding and skills needed to work and teach with modern data.
Danny Kaplan ponders at #StatPREP
One of the most interesting aspects of these workshops were the tutorials and exercises that the participants worked on.
Part of the reason why we have been somewhat silent at Citizen Statistician is that it’s DataFest season, and that means a few weeks (months?) of all consuming organization followed by a weekend of super fun data immersion and exhaustion… Each year that I organize DataFest I tell myself “next year, I’ll do [blah] to make my life easier”. This year I finally did it! Read about how I’ve been streamlining the process of registrations, registration confirmations, and dissemination of information prior to the event on my post titled “Organizing DataFest the tidy way” on the R Views blog.
I meant to write this post last year when I was teaching a large course with lots of teaching assistants to manage, but, well, I was teaching a large course with lots of teaching assistants to manage, so I ran out of time…
There is nothing all that revolutionary here. People have been using Slack to manage teams for a while now. I’ve even come across some articles / posts on using Slack as a course discussion forum, so use of Slack in an educational setting is not all that new either.
On the first day of an intro stats or intro data science course I enjoy giving some accessible real data examples, instead of spending the whole time going over the syllabus (which is necessary in my opinion, but somewhat boring nonetheless).
One of my favorite examples is How to Tell Someone’s Age When All You Know Is Her Name from FiveThirtyEight. As an added bonus, you can use this example to get to know some students' names.
Ok, they’re not hickies, but NPR referred to them as such, so I’m going with it… I’m talking about the cupping marks.
The NPR story can be heard (or read) here. There were two points made in this story that I think would be useful and fun to discuss in a stats course.
The first is the placebo effect. Often times in intro stats courses the placebo effect is mentioned as something undesirable that must be controlled for.
The ASA’s most recent curriculum guidelines emphasize the increasing importance of data science, real applications, model diversity, and communication / teamwork in undergraduate education. In an effort to highlight recent efforts inspired by these guidelines, I organized a JSM session titled Doing more with data in and outside the undergraduate classroom. This session featured talks on recent curricular and extra-curricular efforts in this vein, with a particular emphasis on challenging students with real and complex data and data analysis.
Monday morning at JSM 2016 Andrew Bray and I hosted a roundtable on integrating open access and open source statistics education materials. It was a fruitful discussion with participants from 2-year colleges, 4-year colleges, and industry.
In preparation for the roundtable we put together a one-page handout listing a sampling of open access and open source statistics resources, with links to the resources. The handout is below for anyone who is interested (click on the image to get to the PDF with hyperlinks), and if you think of other resources that would be useful to list here, please comment below and I’ll periodically update list.
