Chris Pirillo » StateStats http://chris.pirillo.com News and Reviews! Geek, Internet Entrepreneur, Hardware Addict, Software Junkie, Book Author, Once TV Show Host, Technology Enthusiast, Shameless Self-Promoter, Tech Conference Coordinator, Early Adopter, Idea Evangelist, Tech Support Blogger, Bootstrapper, Media Personality, Technology Consultant, Thicker Quicker Picker Upper. Mon, 23 Nov 2009 07:06:54 +0000 http://wordpress.org/?v=2.8.5 en hourly 1 © chris@pirillo.com () chris@pirillo.com() Geek, Internet Entrepreneur, Hardware Addict, Software Junkie, Book Author, Once TV Show Host, Technology Enthusiast, Shameless Self-Promoter, Tech Conference Coordinator, Early Adopter, Idea Evangelist, Tech Support Blogger, Bootstrapper, Media Personality, Technology Consultant, Thicker Quicker Picker Upper. chris@pirillo.com No no http://chris.pirillo.com/wp-content/plugins/podpress/images/powered_by_podpress.jpgChris Pirillohttp://chris.pirillo.com 144 144 How Do Your State’s Search Statistics Stack Up?http://chris.pirillo.com/how-do-your-states-search-statistics-stack-up/ http://chris.pirillo.com/how-do-your-states-search-statistics-stack-up/#comments Thu, 27 Nov 2008 08:40:28 +0000 Chris http://chris.pirillo.com/?p=9729 How Do Your State’s Search Statistics Stack Up? is a post from Chris Pirillo

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What was the last thing you searched for on Google? Do you know what your neighbors search for? How is the data of your area’s searches correlated with other sets of data that’s relevant to your state? StateStats allows you to explore the popularity of search results in US States.

This tool shows you how popular a Google search query is in each U.S. state, giving a ranking like the one you see in the left column. It then compares this ranking with other ways of ranking states, like average income or population density, using Spearman’s rank correlation. The middle column shows the results of these comparisons, with the strongest correlations listed first. High numbers (close to 1.0) mean that the rankings “line up” closely, which may indicate a relationship between the search query and the ranking metric.

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.

It’s really interesting to see what people in different places search for the most. I was surprised by some of the results, and I’m sure you will be, as well.

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]]> How Do Your State’s Search Statistics Stack Up? is a post from Chris Pirillo

Add to iTunes | Add to YouTube | Add to Google | RSS Feed

What was the last thing you searched for on Google? Do you know what your neighbors search for? How is the data of your area’s searches correlated with other sets of data that’s relevant to your state? StateStats allows you to explore the popularity of search results in US States.

This tool shows you how popular a Google search query is in each U.S. state, giving a ranking like the one you see in the left column. It then compares this ranking with other ways of ranking states, like average income or population density, using Spearman’s rank correlation. The middle column shows the results of these comparisons, with the strongest correlations listed first. High numbers (close to 1.0) mean that the rankings “line up” closely, which may indicate a relationship between the search query and the ranking metric.

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.

It’s really interesting to see what people in different places search for the most. I was surprised by some of the results, and I’m sure you will be, as well.

Want to embed this video on your own site, blog, or forum? Use this code or download the video:

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