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Calculating the standard deviation in MySQL is a no-brainer by using the build-in aggregate function STDDEV(). If you don't need the original data and only want to save aggregated values in your database, the whole matter is getting more complicated - but is worth from a space and performance point of view.
Since I use MySQL for the statistical analysis on a project, I wanted to optimize the database queries and learned a lot about stuff like number theory, set theory and partial sums. I took my MySQL UDF, I've published two years ago, for this purpose and added new functions for a deeper statistical analysis. The project is around for a while, so it's time to share things with the public to start a discussion of how things could be further optimized. The source and a small documentation can be found on Github:
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When I celebrated my birthday, I got the idea that there must theoretically be a date on which two peoples ages are in a certain ratio. The basic idea were born when I thought that there must be a date on which my mother is exactly twice as old as me. Actually, this is the point of time when I'm as old as my mother was, when I were born. That means
In mathematics, a monotonic function (or monotone function) is a function which preserves the given order. [Wikipedia]
To be more precise, a function f is monotonic increasing, if for every x ≤ y it holds that f(x) ≤ f(y). f is said to be strictly monotonic increasing is for every x < y it holds that f(x) < f(y).
So, if we follow values in some order, we say that f is monotonic increasing if f’s value never decreases (it either increases or stays the same), and we say that f is strictly increasing if f’s value is always changes “upwards”.
Monotonic functions play an important role in SQL. To discuss monotonic functions
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