Lies, damn lies, etc.

An hour long talk about library statistics. It could not sound any more boring, but when colleague A. started talking it was anything but. I think this was because she is a mathematician only in name. Her heart is in letters, not numbers so she is able to tell the stories to explain the stats. This is very important. I’m not going to tell you what she told me, this would be too dull, I would make mistakes trying to reproduce what she told me and even though I did learn some things about the library those weren’t the lesson I learned yesterday.

The most important thing was that data in large data sets is often anything but uniform. That means that it is almost impossible to say anything true about that data based solely on the numbers. It also means that you can never assume anything based on numbers and that you have to ask the right questions about the numbers. The key to using data properly is to ask the right questions. This means that you do not need to be a mathematician to be a statistician, you need to be good at analysis.

There it is. A simple realization after a rather long winded explanation. I could be good with numbers.


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