I have an unnormalized array of counts for a probability mass function (derived from sampling from the true function). The array should be indexed from 0. 12 is the number of times a 0 occurred in the sample. 199 is the number of times a 1 occurred etc.

```
counts = [12, 199, 3125, 29616, 175426, 662401, 1608671, 2477850, 2441350, 1580290, 709625, 235426, 60899, 12643, 2126, 296, 41, 4, 0, 0]
```

I want to fit a normal approximation to this. My first attempt is to estimate its standard deviation. I normalize it with

```
pmf = counts/sum(counts)
```

But stdm(pmf) is apparently an error.

```
ERROR: MethodError: no method matching stdm(::Array{Float64,1})
```

How can I fit a normal approximation to this data set?