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posted by Jason Kottke  ·  gift link

Search correlations with StateStats

StateStats is hours of fun. It tracks the popularity of Google searches per state and then correlates the results to a variety of metrics. For instance:

Mittens - big in Vermont, Maine, and Minnesota, moderate positive correlation with life expectancy, and moderate negative correlation with violent crime. (Difficult to commit crimes while wearing mittens?)

Nascar - popular in North and South Carolinas, strong positive correlation with obesity, and and moderate negative correlation with same sex couples and income.

Sushi - big in NY and CA, moderate positive correlation with votes for Obama, and moderate negative correlation with votes for Bush.

Gun - moderate positive correlation with suicide and moderate negative correlation with votes for Obama. (Obama is gonna take away your guns but, hey, you’ll live.)

Calender (misspelled) - moderate positive correlation with illiteracy and rainfall and moderate negative correlation with suicide.

Diet - moderate positive correlation with obesity and infant mortality and moderate negative correlation with high school graduation rates.

Kottke - popular in WI and MN, moderate positive correlation with votes for Obama, and moderate negative correlation with votes for Bush.

Cuisine - This was my best attempt at a word with strong correlations but wasn’t overly clustered in an obvious way (e.g. blue/red states, urban/rural, etc.). Strong positive correlation with same sex couples and votes for Obama and strong negative correlation with energy consumption and votes for Bush.

I could do this all day. A note on the site about correlation vs. causality:

Be careful drawing conclusions from this data. For example, the fact that walmart shows a moderate correlation with “Obesity” does not imply that people who search for “walmart” are obese! It only means that states with a high obesity rate tend to have a high rate of users searching for walmart, and vice versa. You should not infer causality from this tool: In the walmart example, the high correlation is driven partly by the fact that both obesity and Walmart stores are prevalent in the southeastern U.S., and these two facts may have independent explanations.

Can you find any searches that show some interesting results? Strong correlations are not that easy to find (although foie gras is a good one). (thx, ben)