# How to Normalize a simulated dataset to fit the actual dataset?

 Sci Advisor P: 2,896 Unfortunately "normalize" is an ambiguous instruction. It might mean to convert each data value $v$ to it's "z-score" by computing $\frac{v - \mu}{\sigma}$ where $\mu$ is the mean of the sample in question ( real or simulated) and $\sigma$ is the standard deviation of the sample. It could mean something as simplistic as converting each data value $v$ to a sort of ranking by computing $\frac{v - v_{min}}{v_{max} - v_{min} }$ where $v_{max}$ and $v_{min}$ are, respectively, the max and min values in the sample. We'd have to know more about what the data and the simulation represent to know what makes sense - (and we'd have to assume the person who told to do this gave sensible advice!). If you use z-scores you can probably defend that choice as a common meaning for "normalize". If both your historgrams had a roughly a bell shaped appearance, I'd guess that this was was your advisor meant.