Archive for the 'Statistical analyses' Category

We are now a^H^H^H^H^H^H^H^H productivity blog

Thursday, February 21st, 2008

I always wondered how people see the academic world from outside. How do we gauge the interest of the general public on what academics have to say (on average)? One easy way to look at this question is to see the how often people will read an article that has the word ‘academic’ on it.

A proxy on what people read nowadays is digg.com. And the tool to see how often people digg academic posts is now available in Dan Zarella’s blog. Given a keyword, the tool will return data on the average number of links accumulated by stories popular on Digg that mentioned that keyword. This is done with 2007 data.

Well, behold what happens when you enter “academic”:

clipboard2_21_2008 _ 19_07_34

And compare it to what you get when you type “productivity”:image

Why is this important? Well, on average, a single digg increases traffic by 0.10%. So a story that gets 3,000 diggs results in an increase in total traffic to the referring site by 300%.

So, from now on we are a^H^H^H^H^H^H^H^H productivity blog :)

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The Difference Between Significant and Not Significant is Not Statistically Significant

Monday, December 11th, 2006

MINDLESS SIGNIFICANCE TESTING

pval

Decision science news has a post on hypothesis testing that I find relevant.

Some well-made points grow old while no one pays attention to them. One of the most embarrassing for social science is its categorical perception of p-values.

Tender of kindred Web site Andrew Gelman and Hal Stern have an article whose name says it all: The Difference Between “Significant” and “Not Significant” is not Itself Statistically Significant.

Link to The Difference Between Significant and Not Significant is Not Statistically Significant

 

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