# Programming-Idioms

Calculate the mean m and the standard deviation s of the list of floating point values data.
New implementation

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Other implementations
``````using System.Linq;
using System.Collections.Generic;``````
``````var m = data.Average();
var s = CalculateStdDev(data);

float CalculateStdDev(IEnumerable<float> values)
{
double ret = 0;

if (values.Count() > 0)
{
double avg = values.Average();
double sum = values.Sum(d => Math.Pow(d - avg, 2));
ret = Math.Sqrt((sum) / values.Count()-1);
}
return (float)ret;
}``````
``````defmodule SD do
import Enum, only: [map: 2, sum: 1]
import :math, only: [sqrt: 1, pow: 2]

def standard_deviation(data) do
m = mean(data)
data |> variance(m) |> mean |> sqrt
end

def mean(data) do
sum(data) / length(data)
end

def variance(data, mean) do
for n <- data, do: pow(n - mean, 2)
end
end

# usage
data = [1,2,3,4]
m = SD.mean(data) # => 2.5
sd = SD.standard_deviation(data) # => 1.118033988749895``````
``````real, allocatable :: data(:)
real :: m, s
...
m = sum( data ) / size( data )
s = sqrt( sum( data**2 ) / size( data ) - m**2 )``````
``import "github.com/gonum/stat"``
``m, s := stat.MeanStdDev(data, nil)``
``````mean dat = sum dat / (fromIntegral \$ length dat)

stddev dat = sqrt . mean \$ map ((**2) . (m -)) dat
where
m = mean dat``````
``uses math;``
``````var
m, s: double;
data: array of double;
...
MeanAndStdDev(data, m, s);
...``````
``use Statistics::Lite qw(mean stddev);``
``````my \$m = mean @data;
my \$s = stddev @data;
``````
``import statistics``
``````m = statistics.mean(data)
sd = statistics.stdev(data)
``````
``````m  = data.sum / data.length.to_f
sd = Math.sqrt data.sum { |n| (m-n)**2 } / data.length.to_f
``````