Datascience

Everyone can now work with data and visualize it. Should you?

tl;dr: I release two useful Howard County election datasets in preparation for future posts. In the coming days and weeks I’ll be posting some analyses of Howard County election results. Unfortunately the data released by the Howard County Board of Elections and the Maryland State Board of Elections is not always in the most useful form for analysis. In particular I was looking for per-precinct turnout statistics for the 2014 general election in Howard County, along with some way to match up precincts with the county council district of which they’re a part. That data is available in the 2014 general election results per precinct/district published by the Howard County Board of Elections, but unfortunately that document is a PDF document. ...

tl;dr: I have fun creating graphs and maps with building permit data from data.howardcountymd.gov. I’ve written previously about the cornucopia of interesting data sets that Howard County government has made available at the data.howardcountymd.gov site. I had some spare time over a long weekend and decided to try analyzing some of that data, including making use of the various map files on the site (under the “Spacial Data (GIS)” tab). ...

tl;dr: As we wait to hear more about Allan Kittleman’s HoCoStat proposal, you don’t have to wait to download lots of useful county-related data at data.howardcountymd.gov. During his (ultimately successful) campaign for Howard County Executive, one of Allan Kittleman’s key proposals was to establish HoCoStat, a program to (in Kittleman’s words), “measure . . . response and process times for various government functions” to help “increase responsiveness, improve efficiency and heighten accountability.” Kittleman’s administration is in its early days, and nothing much has been heard yet about how and when HoCoStat might be implemented. (Even the original HoCoStat proposal has disappeared from Kittleman’s web site as it’s being redesigned, although the Internet archive has a copy.) ...

Following up from my previous post on my experience with Coursera, here are a few links of interest (mostly) relating to online education, with a focus on “competency-based education,” i.e., education directed specifically at teaching people to become competent at one or more tasks or disciplines: “Hire Education: Mastery, Modularization, and the Workforce Revolution” (Michelle Weise and Clayton Christensen). Clayton Christensen is famous for his theory of “disruptive innovation,” which I think is useful not so much as a proven theory but rather as a way to structure plausible narratives about business success or failure. When Christensen fails in his predictions it’s usually because he doesn’t pay attention to things that don’t fit neatly into his preferred narratives. For example, he and co-author Michael Horn previously hyped for-profit education companies and failed to see that for many of them actually educating students was not the point. Rather those companies identified a “head I win, tails you lose” business proposition in “chasing Title IV money [i.e., government-subsidized student loans] in a federal financial aid system ripe for gaming.” This represents a second try by Christensen and his associates to forecast the future of post-secondary education. ...

The last three months or so I’ve been in school (which is why I haven’t been posting as much lately). Not a real bricks-and-mortar school—I’ve been participating in the “Data Science Specialization” series of online courses created by faculty at the Johns Hopkins Bloomberg School of Public Health and offered by Coursera, a startup in the online education space. It’s been an interesting experience, and well worth a blog post. The obvious first question is, why I am doing this? Mainly because I thought it would be fun. I was an applied mathematics (and physics) major in college, enjoyed the courses I had in probability, statistics, stochastic processes, etc., and wanted to revisit what I had learned and (for the most part) forgotten. It’s one of my hobbies—a (bit) more active one than watching TV or reading. Also, I’ve done some minor fiddling about with statistics on the blog (for example, looking at Howard County election data), am thinking about doing some more in the future, and wanted to have a better grounding in how best to do this. Finally, “data scientist” is one of the most hyped job categories in the last few years, and even though I probably won’t have much occasion to use this stuff in my current job it certainly can’t hurt to learn new skills in anticipation of future jobs. ...