Thursday, June 16, 2011

Obesity, Driving, & Unbalanced Regressions

The Economist magazine's daily chart of 15 June 2011 was to do with a recent study on the relationship between obesity and amount of driving. This study is reported in a paper by Jacobson et al. (2011), which is "in press" at the journal, Transport Policy. This paper will bring tears to all econometric eyes! Not tears of joy, either.

There are so many things that one could say about it that it's really difficult to know where to start - but I'll try!

Before we start, though, a word about the charts in the 15 June chart blog in The Economist. There are two of them - look at the one on the left. Are they really plotting the correlation between the two variables in question? I don't think so.  Anyway, that's not my real gripe. My problem is with the paper that's being published by Transport Policy (TP). And judging by the nature of the comments on The Economist's blog, I'm not alone.

From its website, I see that TP has an impact factor of 1.024. This just goes to show how misleading impact factors can be - it's quite possible to get the impact factor above unity simply by publishing material that infuriates people so much that everyone has to cite it in order to take issue with it! Nice trick if you can get away with it!

Google Correlate

There's an interesting piece in the latest issue of The Royal Statistical Society's newsletter, RSSNews. It's about one of Google's new data analysis tools, called Google Correlate. If you haven't come across this, it's worth a look.

You can upload your own time-series data (from a .csv file, say) and then use Google's search history to find what other data your series correlates highly with.

Just keep in mind that "correlation" and "causation" are not the same thing! More on the latter in future posts.

© 2011, David E. Giles