Supreme Court voting patterns

In the past few years, the US Supreme Court has handed down a number of high-profile decisions with a 5-4 majority. In the most recent term, these included the two gay-marriage cases Hollingsworth v. Perry and United States v. Windsor, as well as the voting-rights case Shelby County v. Holder. In the previous term there was one that was perhaps even more of a media event: the “Obamacare decision” in National Federation of Independent Business v. Sebelius.

With each 5-4 decision, people start to talk about how many 5-4 decisions there are, and people seem to think there are more of them than there used to be. There’s also talk about the increasing polarization of the court, because (according to the popular wisdom) so many decisions are not just 5-4, but the same 5-4, with the court divided into conservative and liberal factions that regularly vote en bloc. There seems to be a sentiment that these close decisions are somewhat undesirable, because they indicate a fragility in our system of government. (Or, as some might put it, they serve as uncomfortable reminder of how much influence Anthony Kennedy has on the law.)

Is this true? Are there really more 5-4 decisions than there used to be? Is the court really more polarized than it used to be? Every one of these is an. . . interesting question!!!

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Programming languages: quality, popularity, and versatility

If you haven’t seen The Right Tool, you should check it out. It’s a little web doodad where you can rank programming languages according to how well they’re described by various statements, like “This language is very flexible” or “The thought that I may still be using this language in twenty years time fills me with dread”. It summarizes the results and displays them, letting you see what the consensus view is on each language, which languages are similar to or different from which others, etc.

I saw this a year or so ago, and one thing that intrigued me was the variety in the types of statements on which you could rate the languages. Some of them have an obviously subjective, value-judgment nature, and seem to be evaluating the language on overall quality. Other statements seem to have to do more with how widely-used the language is, independent of how much people like it. Still others describe the language’s suitability for particular tasks.

The Right Tool lets you see how languages compare on a particular statement, or how a particular language stacks up on various statements, and it lets you compare two languages. It also lets you see which statements are “similar to” other statements, in the sense that languages described well by one statement also tend to be described well by another. What it doesn’t do is let you see how languages perform on groups of statements like the ones I just described — i.e., “quality-judgment” statements vs “versatility” statements.

In a happy twist of fate, I recently discovered that raw data from The Right Tool is available. So I decided to use that data for my own nefarious purposes, namely, to see how languages compare when you group the statements into categories and aggregate language rankings within a category. What I wanted to see was whether, for instance, languages that are widely-used are also well-liked, and that sort of thing. Why did I want to see this? Because it’s. . . an interesting question!

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Useful Scrabble words

After reading my last Scrabble post, someone suggested that it would be useful to see a sort of “utilitarian” breakdown of Scrabble words. That is, which words are the most useful to know? Answering this question is trickier than it might seem.

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Scrabble: what makes good players good

I play a lot of Scrabble. In this day and age, it’s often a point of pride for people to say they’re not on Facebook. Well, I’m on Facebook, but most of my time on the site is spent playing other people with the Scrabble app.

I’ve gotten pretty good over the years, but I’m still pretty puny in comparison to the really good players. I often start random-matchup games with other Scrabble users who are total strangers to me, and every once in a while I’ll get matched with one of these heavyweights who just blows me away. More often, I get matched with a lightweight who I just blow away. Sometimes I get matched with a middleweight like me and we rematch each other endlessly.

Inevitably, of course, I found myself wondering: What is it that makes good Scrabble players good? Like, what do they do differently? Do they make more good plays, or fewer bad plays? Is it really true what everyone says about how learning all the 2-letter words is the key to victory? What is it that separates the wheat from the chaff, Scrabble-wise?

Well, that’s an. . . (drumroll) interesting question! And in typical Interesting Question fashion, I decided to try to analyze it by getting my hands on some data.

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Good days, mate

I’ve always been kind of intrigued by climatology and meteorology. Whenever I read Wikipedia articles about random places, I take special interest in looking at the climate section (if there is one) and seeing the little chart and (hopefully) graph of the temperature and precipitation over the course of the year.

I happen to live in a place with a remarkably mild climate. When I was younger I didn’t think much about it, but as I’ve gotten older and met more people from other places I’ve been more struck by how they perceive it. It can be a real shocker for people to come here in mid-January and find people in shorts and T-shirts and going to the beach and whatnot.

Now, the interesting questions I started thinking about are: what is it that makes a place’s climate seem nice, and how common is it for places to have such a climate? I did some thinking about these questions and just sort of operationalized some of my hunches, and then checked out the implications of this using a fairly big set of global weather data.

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