JSM 2017 is almost here. I just landed in Maryland, and I finally managed to finish combing through the entire program. What a packed schedule! I like writing an itinerary post each year, mainly so I can come back to it during and after the event. I obviously won’t make it to all sessions listed for each time slot below, but my decision for which one(s) to attend during any time period will likely depend on proximity to previous session, and potentially also proximity to childcare area.
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.
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.
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.
Ten years after Ioannidis alleged that most scientific findings are false, reproducibility – or lack thereof – has become a full-blown crisis in science. Flagship journals like Nature and Science have published hand-wringing editorials and revised their policies in the hopes of heightening standards of reproducibility. In the statistical and data sciences, the barriers towards reproducibility are far lower, given that our analysis can usually be digitally encoded (e.g., scripts, algorithms, data files, etc.
JSM 2016 is almost here. I just spent an hour going through the (very) lengthy program. I think that was time well spent, though some might argue I should have been working on my talk instead…
Here is what my itinerary looks like as of today. If you know of a session that you think I might be interested in that I missed, please let me know! And if you go to any one of these sessions and not see me there, it means I got distracted by something else (or something close by).
