PI approximation with Monte Carlo Simulation

/**
 * 
 * PI approximation using  Monte Carlo Simulation. Draw a square of
 * unit area on the ground, then inscribe a circle within it. Now, scatter some
 * small objects (for example, grains of rice or sand) throughout the square. If
 * the objects are scattered uniformly, then the proportion of objects within
 * the circle vs objects within the square should be approximately PI/4, which
 * is the ratio of the circle's area to the square's area. Thus, if we count the
 * number of objects in the circle, multiply by four, and divide by the total
 * number of objects in the square (including those in the circle), we get an
 * approximation to PI. (http://en.wikipedia.org/wiki/Monte_Carlo_method)
 * 
 */
public class PiEstimationWithMonteCarlo {

 public double estimatePI(long numberSample) {
     long numberInCircle = 0;
     double pi = 0.0;

     for (int i = 0; i < numberSample; i++) {
         double x = generateRandomNumber();
         double y = generateRandomNumber();
         if (insideCircle(x, y))
             numberInCircle++;
     }
     pi = (numberInCircle * 4) / ((double) numberSample);
     return pi;
 }

 private boolean insideCircle(double x, double y) {
     double distance = x * x + y * y;
     if (distance > 1) {
         // out of circle
         return false;
     }
     return true;
 }

 private double generateRandomNumber() {
     // between -1 and 1
     return Math.random() * 2 - 1;
 }

 public static void main(String args[]) {
     PiEstimationWithMonteCarlo piEstimator = new PiEstimationWithMonteCarlo();
     double pi = piEstimator.estimatePI(5000000);
     System.out.println("PI=" + pi);
 }
}