Walking It Back

My last post was surprisingly popular—and not just among people who know me personally. I even managed to pick up a few new followers, who I’m afraid will be put off a bit when they discover travel writing isn’t aligned the usual subjects of this blog (but hopefully not!).

Anyway, as you may or may not recall, the last post incorporated a graph of the distance I’d walked the days before, during, and after various legs of my trip through Italy:

miles walked

In the graph’s caption, I glibly blamed my apparent sedentarism on my office job and commute. I like to think of myself as a decently fit person, you see. Surely, I reasoned, my desk job must be impeding an otherwise active lifestyle. I mean, I have a standing desk—clearly I’m a man who values his physical fitness.

It occurred to my a few days later that my hypothesis was actually pretty testable: if work and commuting were really to blame, my weekends should be significantly more active (measured by distance walked/run) than average. Apple has, for some reason, elected to make exporting health data from iPhones an incredibly difficult process. So, with the zeal of an intern, I manually entered 242 days worth of mileage, attempting to evidence my claim.

Looking back, my naiveté was almost cute. In the era of “binge-watching,” I really believed myself exceptional.

The raw data is pretty depressing. The mean distance walked is 1.54 miles. But the data is right-skewed, meaning outliers on the upper end of the distribution are pulling the mean higher. (The median distance walked over this period is a shockingly low .985 miles.) It’s also telling that the distribution isn’t bimodal, which would indicate two distinct populations—in the case of my hypothesis, weekdays and weekends.

Miles Walked histboxmiles

I could have quit here, but I’ve touched on the importance of publishing negative results before and therefore had a cross to bear. To make the data set more normal, I removed outliers (in this case, all values greater than 3.73 miles) and used a square-root transformation:

Square Root Miles Walked, no outliers

The means of our new, outlier-free population and the “weekend” sample (n=61) are, respectively, 1.023² miles and 1.046² miles, and the population standard deviation is .377² miles. At the 95% confidence level, the sample would have to have a mean of about 1.106² miles to be statistically higher than the average.

It is with great shame that I reject the alternate hypothesis. And I do hereby humbly apologize to office life for blaming it for what is clearly a personal shortcoming.

A few caveats, in case my health insurance provider is reading:

  • I do exercise most days before work. But mostly pull-ups, lunges, and other anaerobic stuff. I only run sporadically—and when I do, I don’t always bring my phone with me.
  • I can’t vouch for the accuracy of the iPhone’s pedometer. Anecdotally, I’ve heard it isn’t great, and light research confirms it has trouble measuring steps under some common conditions, like being held or kept in a backpack.
  • The combination of the above suggests iPhone health data offers a convenient but incomplete metric to assess one’s activity. For example, July 31, a day my phone credits me with walking 4.7 miles, also happens to be a day I went for a 30-mile bike ride.
  • Including Fridays in the “weekend” sample raises the mean distance slightly, to 1.08 miles, but still not enough to achieve statistical significance.
  • Uh, I will try to do better.
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The CBO Feels the Love

The Congressional Budget Office isn’t known for its awesome marketing or pithy statements. It’s never been recognized by Buzz Feed for its social media use. Nevertheless, the Congressional Budget Office (CBO) is enjoying an unusual amount of love on Twitter.

Here’s how you really know they’ve made it: The title of yesterday’s National Review Morning Jolt was, “The Congressional Box Office is Very ‘In’ Right Now.”

Two nights ago, it tweeted a four-word message with a link to its analysis of the American Health Care Act (AHCA) that has received far more attention than is normal for the CBO twitter account. As of writing this post, the tweet in question has racked up 62 responses, 846 retweets, and 542 likes.

That might not sound like a lot; the truth is, it isn’t. Donal Trump’s tweets, for example, often receive tens of thousands of ‘likes.’ But relative to the usual engagement on the CBO’s tweets, it’s absolutely ridiculous.

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Since January first of 2016, the CBO has tweeted 120 times. The median numbers of responses, retweets, and ‘likes’ to those tweets were respectively 0, 3, and 2. In fact, this latest tweet is responsible for nearly half of all the reactions garnered by the CBO’s account over that time period.

So what does this tell us?

The most obvious insight is that people are paying more attention to the CBO since the administration change. That’s not surprising; the CBO evaluates economic and budget proposals, and there are quite a few shakeups going on in that department right about now. The agency has been firing on all cylinders to keep up with demands from Congress, doubling the frequency of its tweets since Trump took office (.48 tweets/day compared with .24 tweets/day during the previous year).

In the final year of Barack Obama’s presidency, the CBO only averaged 9.5 ‘retweets’ per tweet–and that’s including a January 17th tweet that was responsible for 405 retweets alone (if you exclude that post, the account averaged 5 retweets per post). Since the beginning of the Trump administration, that average has jumped to 39.6 (7.6 if you don’t include the latest viral tweet).

Another insight: Negative feelings about the AHCA are driving the CBO’s recent popularity surge. The only two tweets with significant activity in the past year (look at the spikes in the graphs above) were about the AHCA and the effects of repealing the Affordable Care Act (ACA). A cursory glance through the responses to both tweets reveals that most of the commenters are detractors of the current administration who oppose changes to the ACA.

It would be a mistake to use this as a proxy for national consensus on the AHCA, however. Twitter often skews liberal.

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For the record, the CBO writes a killer blog (I use the term loosely, for obvious reasons). It’s a great source of unfiltered information about economic ideas from Washington. You can sign up to receive email updates from it here. And, if the CBO is reading this, don’t forget about us when you get famous.