Just finished a stimulating, thought-provoking week at SRTL —Statistics Research Teaching and Learning conference–this year held in Two Harbors Minnesota, right on Lake Superior. SRTL gathers statistics education researchers, most of whom come with cognitive or educational psychology credentials, every two years. It’s more of a forum for thinking and collaborating than it is a platform for presenting findings, and this means there’s much lively, constructive discussion about works in progress.
The other day I was painting the trim on our house and it got me reminiscing. The year was 2005. The conference was JSM. The location was Minneapolis. I had just finished my third year of graduate school and was slotted to present in a Topic Contributed session at my first JSM. The topic was Implementing the GAISE Guidelines in College Statistics Courses. My presentation was entitled, Using GAISE to Create a Better Introductory Statistics Course.
Two years ago, my department created a new two-course, doctoral-level sequence primarily aimed at our quantitative methods students. This sequence, aside from our students, also attracts students from other departments (primarily in the social sciences) that plan to pursue more advanced methodological coursework (e.g., Hierarchical Linear Modeling).
One of the primary characteristics that differentiates this new sequence of courses from the other doctoral sequence of methodology courses that we teach is that it is “more rigorous”.
The Mobilize project, which I recently joined, centers a high school data-science curriculum around participatory sensing data. What is participatory sensing, you ask?
I’ve recently been trying to answer this question, with mixed success. As the name suggests, PS data has to do with data collected from sensors, and so it has a streaming aspect to it. I like to think of it as observations on a living object. Like all living objects, whatever this thing is that’s being observed, it changes, sometimes slowly, sometimes rapidly.
From Jasper Fforde’s latest Thursday Next novel (The Woman Who Died Alot):
The Office for Ultimate Risk is one of the many departments within the Ministry of National Statistics. Although it was originally an “experimental” department, the statisticians at Ultimate Risk proved their worth by predicting the entire results of three football World Cups in succession, a finding that led to the discontinuation of football as a game and the results being calculated instead.
In Emanuel Derman’s book Models. Behaving. Badly, the author lays out a Modeler’s Hippocratic Oath.
I will remember that I didn’t make the world, and it doesn’t satisfy my equations.
Though I will use models boldly to estimate value, I will not be overly impressed by mathematics.
I will never sacrifice reality for elegance without explaining why I have done so.
Nor will I give the people who use my model false comfort about its accuracy.
