Accurately compute variance and standard deviation in one pass. Source: http://www.johndcook.com/blog/2013/06/11/computing-skewness-and-kurtosis-in-one-pass/

variance.cpp

 class RunningStat
    {
    public:
        RunningStat() : m_n(0) {}

        void Clear()
        {
            m_n = 0;
        }

        void Push(double x)
        {
            m_n++;

            // See Knuth TAOCP vol 2, 3rd edition, page 232
            if (m_n == 1)
            {
                m_oldM = m_newM = x;
                m_oldS = 0.0;
            }
            else
            {
                m_newM = m_oldM + (x - m_oldM)/m_n;
                m_newS = m_oldS + (x - m_oldM)*(x - m_newM);
    
                // set up for next iteration
                m_oldM = m_newM; 
                m_oldS = m_newS;
            }
        }

        int NumDataValues() const
        {
            return m_n;
        }

        double Mean() const
        {
            return (m_n > 0) ? m_newM : 0.0;
        }

        double Variance() const
        {
            return ( (m_n > 1) ? m_newS/(m_n - 1) : 0.0 );
        }

        double StandardDeviation() const
        {
            return sqrt( Variance() );
        }

    private:
        int m_n;
        double m_oldM, m_newM, m_oldS, m_newS;
    };

 int main()
    {
        RunningStat rs;

        rs.Push(17.0);
        rs.Push(19.0);
        rs.Push(24.0);

        double mean = rs.Mean();
        double variance = rs.Variance();
        double stdev = rs.StandardDeviation();
    }