The other day on the isostat mailing list Doug Andrews asked the following question:
Which R packages do you consider the most helpful and essential for undergrad stat ed? I ask in great part because it would help my local IT guru set up the way our network makes software available in our computer classrooms, but also just from curiosity. Doug asked for a top 10 list, and a few people have already chimed in with great suggestions.
Somehow almost an entire academic year went by without a blog post, I must have been busy… It’s time to get back in the saddle! (I’m using the classical definition of this idiom here, “doing something you stopped doing for a period of time”, not the urban dictionary definition, “when you are back to doing what you do best”, as I really don’t think writing blog posts are what I do best…)
One big challenge we all face is understanding what’s good and what’s bad for us. And it’s harder when published research studies conflict. And so thanks to Roger Peng for posting on his Facebook page an article that led me to this article by Emily Oster: Cellphones Do Not Give You Brain Cancer, from the good folks at the 538 blog. I think this article would make a great classroom discussion, particularly if, before showing your students the article, they themselves brainstormed several possible experimental designs and discussed strengths and weaknesses of the designs.
Yup. You read it here first. The National Climatic Data Center has a nice overview that compares climate data to Punxsutawney Phil’s predictions. The data aren’t quite (yet) upload-ready, but some links on the page to more raw data might be entertaining.
Last Saturday the Mobilize project hosted a day-long professional development meeting for about 10 high school math teachers and 10 high school science teachers. As always, it was very impressive how dedicated the teachers were, but I was particularly impressed by their creativity as, again and again, they demonstrated that they were able to take our lessons and add dimension to them that I, at least, didn’t initially see.
One important component of Mobilize is to teach the teachers statistical reasoning.
I’m very excited/curious about tomorrow: I’m going to lead about 40 math and science teachers in a data-analysis activities, using one of the Model Eliciting Activities from the University of Minnesota Catalysts for Change Project. (One of our bloggers, Andy, was part of this project.) Specifically, we’re giving them the arrival-delay times for five different airlines into Chicago O’Hare. A random sample of 10 from each airline, and asking them to come up with rules for ranking the airlines from best to worst.
Apparently our last blog post was in August. Dang. Where did five months go? Blog guilt would be killing me, but I swear it was just yesterday that Mine posted.
I will give a bit of review of some of the books that I read this semester related to statistics. Most recently, I finished Hands-On Matrix Algebra Using R: Active and Motivated Learning with Applications. This was a fairly readable book for those looking to understand a bit of matrix algebra.
