Recently the blog Brain Pickings wrote about the set of hand-drawn visualizations that Civil Rights activist W.E.B. Du Bois commissioned for the1900 World’s Fair in Paris. (In a previous post, Rob wrote about an art exhibit he saw that featured artistic interpretations of these plots.) Every time I see these visualizations I am amazed—they are gorgeous and the detail (and penmanship) is amazing. The visualizations included bar charts, area plots, and maps—all hand-drawn!
One of the many nice things about summer is the time and space it allows for blogging. And, after a very stimulating SRTL conference (Statistics Reasoning, Teaching and Learning) in Rotorua, New Zealand, there’s lots to blog about. Let’s begin with a provocative posting by fellow SRTL-er Tim Erickson at his excellent blog A Best Case Scenario. I’ve known Tim for quite awhile, and have enjoyed many interesting and challenging discussions.
After reading this review of a Theaster Gates show at Regan Projects, in L.A., I hurried to see the show before it closed. Inspired by sociologist and civil rights activist W.E.B. Du Bois, Gates created artistic interpretations of statistical graphics that Du Bois had produced for an exhibition in Paris in 1900. Coincidentally, I had just heard about these graphics the previous week at the Data Science Education Technology conference while evesdropping on a conversation Andy Zieffler was having with someone else.
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.
As a statistician who often needs to explain methods and results of analyses to non-statisticians, I have been receptive to the influx of literature related to the use of storytelling or a data narrative. (I am also aware of the backlash related to use of the word “storytelling” in regards to scientific analysis, although I am less concerned about this than, say, these scholars.) As a teacher of data analysis, the use of narrative is especially poignant in that it ties the analyses performed intrinsically to the data context—or at the very least, to a logical flow of methods used.
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