The Box-Cox Transformation

The Box-Cox transformation is a family of power transform functions that are used to stabilize variance and make a dataset look more like a normal distribution. Lots of useful tools require normal-like data in order to be effective, so by using the Box-Cox transformation on your wonky-looking dataset you can then utilize some of these tools.

Here’s the transformation in its basic form. For value x and parameter \lambda:

\displaystyle \frac{x^{\lambda}-1}{\lambda} \quad \text{if} \quad x\neq 0 

\displaystyle log(x) \quad \text{if} \quad x=0

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