Andrew Gelman on Blogging (part 3 of 3)

What have you learned about blogging?

I’m surprised that there are no other statistics blogs. Chris Genovese used to do one but he stopped–and his blog was more personal than mine, less about statistics. I’ve tried to stay on topic (most of the time), since that’s what I have to offer. I have political opinions, cute stories about my kids, etc., but why should anyone care about this?

I’m also surprised there are so many blogs about economics. Especially since psychology is more interesting (to me). Is this just path-dependence, or maybe actually there are a lot of other blogs out there that I don’t know about. I read some econ blogs partly from clicking my link to Alex’s Marginal Revolution blog which links to others. There are also a lot of tech blogs and computer science blogs but this is less surprising given that it’s on a computer. I suppose there are also lots of blogs about current TV shows and so forth that I don’t really have interest in. As it is, I already read too many blogs. I’m trying to spend more time reading the newspaper. Regarding my own blog, first I was surprised that my students/postdocs/colleagues had so little interest in posting, second I was surprised at how few comments I get on most entries. I don’t always know what will get comments, actually. I’ve had some success using the blog as a sort of out-box where I can park my ideas, but it’s not a panacea. For one thing, it means I spend more time on the computer, which is hard on my hands and maybe degrades my general work productivity.

It’s fun having 1000 readers a day (whatever that means; as a statistical consumer I’m remarkably uncurious about where the numbers come from. One day my postdoc discovered that we had set a switch wrong on the counter, and it turned out we had 1000 rather than 500 per day) although it’s hard for me to think if that’s a lot or a little. Many of my favorite statistical ideas have had struggles with acceptance (for example, there are still a lot of statisticians, even Bayesians, who fit models without even trying to see if they produce replications that look like observed data) so the proselytizer in me wants that large audience.

Finally, I’ve learned that writing can be easier than reading. As is illustrated by the above response that I’ve spewed out.

Parts 1 and 2 of this interview.

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