“How much is your education worth to you?!? E-mail your best offer.”

5423-doonsebury.pngArticle from the Chronicle of Higher Education about course selection (competition, class lotteries, etc).

Every college has a hot-ticket class. Maybe it’s the subject matter (serial killers! sailing!) or maybe it’s a celebrity professor (George Tenet! Toni Morrison!). Whatever it is, everybody wants to get in.

And, of course, not everybody can. So how do you decide who gets a seat and who’s disappointed?

If you’re Patricia de Castries, you make everybody sleep outside your door. Ms. de Castries, assistant director of the Stanford Language Center, teaches a wildly popular wine-tasting course at the university. Often more than 100 would-be connoisseurs compete for the 60 spots, so on the eve of registration students show up with pillows and sleeping bags, hoping to get their names on the list. “It’s tough,” says Ms. de Castries, “but if you want to be in the class, you do it.”

Covers the range from MIT’s technical approach to Wharton’s free market approach, where students at the latter bid on courses using a point system. Sadly, the article now seems to be blocked except for those academic-types who have access to a subscription.

(Thanks Eugene)

Sunday, March 9, 2008 | probability  

Visualizing Data Book CoverVisualizing Data is my 2007 book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. When first published, it was the only book(s) for people who wanted to learn how to actually build a data visualization in code.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is the basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.