How to fit a normal approximation to data in Julia

Specific Domains Statistics
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Three approaches that occur to me are

  1. matching moments: calculate weighted mean and variance using GitHub - JuliaStats/StatsBase.jl: Basic statistics for Julia (your counts are a weight vector)

  2. the same with some quantile statistics (eg 25-75%)

  3. maximum likelihood, or likelihood-based methods in general: given a mean and a standard deviation you can calculate the log likelihood of each value, counts multiply that

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