Calculating Standard Deviation & Variance in C++

Here's another approach using std::accumulate but without using pow. In addition, we can use an anonymous function to define how to calculate the variance after we calculate the mean. Note that this computes the unbiased sample variance.

#include <vector>
#include <algorithm>
#include <numeric>

template<typename T>
T variance(const std::vector<T> &vec) {
    const size_t sz = vec.size();
    if (sz == 1) {
        return 0.0;
    }

    // Calculate the mean
    const T mean = std::accumulate(vec.begin(), vec.end(), 0.0) / sz;

    // Now calculate the variance
    auto variance_func = [&mean, &sz](T accumulator, const T& val) {
        return accumulator + ((val - mean)*(val - mean) / (sz - 1));
    };

    return std::accumulate(vec.begin(), vec.end(), 0.0, variance_func);
}

A sample of how to use this function:

#include <iostream>
int main() {
    const std::vector<double> vec = {1.0, 5.0, 6.0, 3.0, 4.5};
    std::cout << variance(vec) << std::endl;
}

As the other answer by horseshoe correctly suggests, you will have to use a loop to calculate variance otherwise the statement

var = ((Array[n] - mean) * (Array[n] - mean)) / numPoints;

will just consider a single element from the array.

Just improved horseshoe's suggested code:

var = 0;
for( n = 0; n < numPoints; n++ )
{
  var += (Array[n] - mean) * (Array[n] - mean);
}
var /= numPoints;
sd = sqrt(var);

Your sum works fine even without using loop because you are using accumulate function which already has a loop inside it, but which is not evident in the code, take a look at the equivalent behavior of accumulate for a clear understanding of what it is doing.

Note: X ?= Y is short for X = X ? Y where ? can be any operator. Also you can use pow(Array[n] - mean, 2) to take the square instead of multiplying it by itself making it more tidy.

Your variance calculation is outside the loop and thus it is only based on the n== 100 value. You need an additional loop.

You need:

var = 0;
n=0;
while (n<numPoints){
   var = var + ((Array[n] - mean) * (Array[n] - mean));
   n++;
}
var /= numPoints;
sd = sqrt(var);

Two simple methods to calculate Standard Deviation & Variance in C++.

#include <math.h>
#include <vector>

double StandardDeviation(std::vector<double>);
double Variance(std::vector<double>);

int main()
{
     std::vector<double> samples;
     samples.push_back(2.0);
     samples.push_back(3.0);
     samples.push_back(4.0);
     samples.push_back(5.0);
     samples.push_back(6.0);
     samples.push_back(7.0);

     double std = StandardDeviation(samples);
     return 0;
}

double StandardDeviation(std::vector<double> samples)
{
     return sqrt(Variance(samples));
}

double Variance(std::vector<double> samples)
{
     int size = samples.size();

     double variance = 0;
     double t = samples[0];
     for (int i = 1; i < size; i++)
     {
          t += samples[i];
          double diff = ((i + 1) * samples[i]) - t;
          variance += (diff * diff) / ((i + 1.0) *i);
     }

     return variance / (size - 1);
}