How to compute Pearson Correlation between 2 given vectors?

Question

I have to code this in C#

Can you explain step by step in the below given example?

vector 1 : [0.3, 0, 1.7, 2.2]
vector 2 : [0, 3.3, 1.2, 0]

Ty very much

This will be used in document clustering

Answer 1

That's adaptation of my answer on Java version

How to find correlation between two integer arrays in java

for C#. First, the Pearson Correlation is

http://en.wikipedia.org/wiki/Correlation_and_dependence

Providing that both vectors (let them be IEnumerable<Double>) are of same length

  private static double Correlation(IEnumerable<Double> xs, IEnumerable<Double> ys) {
    // sums of x, y, x squared etc.
    double sx = 0.0;
    double sy = 0.0;
    double sxx = 0.0;
    double syy = 0.0;
    double sxy = 0.0;

    int n = 0;

    using (var enX = xs.GetEnumerator()) {
      using (var enY = ys.GetEnumerator()) {
        while (enX.MoveNext() && enY.MoveNext()) {
          double x = enX.Current;
          double y = enY.Current;

          n += 1;
          sx += x;
          sy += y;
          sxx += x * x;
          syy += y * y;
          sxy += x * y;
        }
      }
    }

    // covariation
    double cov = sxy / n - sx * sy / n / n;
    // standard error of x
    double sigmaX = Math.Sqrt(sxx / n -  sx * sx / n / n);
    // standard error of y
    double sigmaY = Math.Sqrt(syy / n -  sy * sy / n / n);

    // correlation is just a normalized covariation
    return cov / sigmaX / sigmaY;
  }

Test:

  // -0.539354840012899
  Double result = Correlation(
    new Double[] { 0.3, 0, 1.7, 2.2 }, 
    new Double[] { 0, 3.3, 1.2, 0 });