Decision Mechanics

Insight. Applied.

What Nathan Yau uses to visualize data

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Nathan Yau of FlowingData has published an up-to-date list of what he uses to turn raw data into his impressive visualizations.

What’s always striking about the tools he uses is that there’s no “quick fix”. He utilizes a range of industry standard data manipulation (e.g. R) and graphic design (e.g. Adobe Illustrator) tools in his work.

I particularly liked his comments on processing and formatting data

Assuming I have the data I want (big assumption), this is a stage of tedium. Solutions typically reflect my state of I-want-this-to-be-done-already, and I use whatever tool is closest. I would use a hammer if I could.

Statisticians publish guidance on p-values

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American Statistical Association building

The American Statistical Association has taken the unprecedented step of issuing guidance on the use of p-values. Its statement was prompted by concerns that misuse of p-values was driving bad science.

Basic and Applied Social Psychology has refused to accept papers containing p-values.

A p-value is “informally” defined in the statement as

…the probability under a specified statistical model that a statistical summary of the data (for example, the sample mean difference between two compared groups) would be equal to or more extreme than its observed value.

Doesn’t really help much, but you have to applaud the attempt. After all, even scientists don’t really understand p-values.