CoolData blog

29 May 2014

Nate Silver on age-guessing from first names

Filed under: CoolData — Tags: , , — kevinmacdonell @ 3:22 pm

Friend and colleague Greg Pemberton (@GregPemberton) pointed me to this interesting post on the FiveThirtyEight blog: How to Tell Someone’s Age When All You Know Is Her Name. Wow, I thought … that rings a bell! I wrote a blog post on exactly that topic: How to infer age, when all you have is a name. That was nearly four years ago, and I’ve written a couple more posts on the subject since then.

I’m not suggesting that there’s any borrowing going on. The idea is hardly rocket science and has undoubtedly occurred to many people independently long before I got my noggin around it. So why am I posting this?


I am a fan of Nate Silver and his blog. I devoured his book, “The Signal and the Noise,” shortly after it came out. And last year I dragged my butt out of bed in the early morning after an awesome conference reception with multiple open bars to hear him deliver a keynote address. So I was very interested to read his post, co-authored with Allison McCann.

And yes, I may also have been interested in posting a comment in response, with links to CoolData. I am a blogger, after all. So I carefully prepared my comment, and hit ‘Go’. What happened then? A Facebook fail!


Really, Nate? I need a Facebook account to post a comment? I shut down my Facebook account years ago, for all sorts of reasons, and I don’t plan to go back. (Maybe I shouldn’t criticize. People can’t leave comments on CoolData at all. But Facebook??)

My comment needs a home. Why not right here? Thank you for reading.

I use these age/name/sex patterns to infer likely age in our university database work. We already know the name, gender and age for most people, so we can calculate mean and median ages for all combinations of name and sex, and apply those to any new records that are lacking this data (such as prospective donors). This is helpful, as ‘age’ is strongly correlated with likelihood to make a donation and the size of the gift. Gender can be an important factor … A number of first names have “flipped gender”, so they either belong to a relatively old man or a relatively young female. Examples I know of include Ainslie, Isadore, Sydney, Shelly, and Brooke.

I have written about this a few times:

How to infer age, when all you have is a name

New twists on inferring age from first name

Putting an age-guessing trick to the test



On re-reading the FiveThirtyEight post, I was struck by this passage, which I didn’t notice earlier: “There are quite a lot of websites devoted to tracking the popularity of American baby names over time. … But we haven’t seen anyone ask the age of living Americans with a given name.”

Oh really. … Let me Google that for you.



When I first posted the “Let me Google that for you” link, CoolData was at the top of the results. It has since been crowded out by FiveThirtyEight and others. The benefits of a large web presence and the resources to optimize search results.



One thing was puzzling me … In my stats, I have seen a lot of people clicking on the link to FiveThirtyEight from my blog, but I also noticed that almost 200 people (to date) have come to CoolData from FiveThirtyEight. I couldn’t figure out how — there was no link to CoolData that I could find. Well, I’ve found it. CoolData is referenced in the first footnote below the FiveThirtyEight post on age-guessing from names. One has to click the plus sign in the circle (before the comments) to see the footnotes. So — thanks, Nate!



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