Below is a simple set of classes for performing your own statistical analysis. As noted, they are simple (no multiple regressions analysis, etc.)

class myStats {
double standardDeviation (double[] array) {
 double[] arr = new double[array.length];
 double av = average(array);
  for (int i = 0; i < array.length; i++) {
    arr[i] = (array[i] - av) * (array[i] - av);
 }
 double d = 0;
  for (int i = 0; i < array.length; i++) {
    d = d + arr[i];
 }
 return Math.sqrt(d / (arr.length - 1));
}

double correlation (double[] array1, double[] array2) {
 double[] arr = new double[array1.length];
 double av1 = average(array1);
 double av2 = average(array2);
  for (int i = 0; i < array1.length; i++) {
    arr[i] = (array1[i] - av1) * (array2[i] - av2);
 }
 double d = 0;
  for (int i = 0; i < array1.length; i++) {
    d = d + arr[i];
 }
 double sd1 = standardDeviation(array1);
 double sd2 = standardDeviation(array2);
 return (d / (sd1 * sd2)) / (array1.length - 1);
}

double slope (double[] array1, double[] array2) {
 double[] arr = new double[array1.length];
 double av1 = average(array1);
 double av2 = average(array2);
  for (int i = 0; i < array1.length; i++) {
    arr[i] = (array1[i] - av1) * (array2[i] - av2);
 }
 double d = 0;
  for (int i = 0; i < array1.length; i++) {
    d = d + arr[i];
 }
 double sd1 = standardDeviation(array1);
 double sd2 = standardDeviation(array2);
 return (sd1 / sd2) * correlation(array1,array2);
}

double yIntercept(double array1[], double array2[]) {
 double d = 0;
 double sl = slope(array1, array2);
 double yAvg = average(array1);
 double xAvg = average(array2);
 d = yAvg - (sl * xAvg);
 return d;
}

double average(double array[]) {
 double d = 0;
 double total = 0;
  for (int i = 0; i < array.length; i++) {
    total = total + array[i];
 }
 d = total / array.length;
 return d;
}

double lineFit(double array1[], double array2[]) {
 double yAvg = average(array1);
 double sl = slope(array1, array2);
 double yi  = yIntercept(array1, array2);
 double d1 = 0;
 double squaredResidual = 0;
 double squaredYVariance = 0;
 for (int i = 0; i < array1.length; i++) {
    squaredYVariance = squaredYVariance + ((array1[i] - yAvg) * (array1[i] - yAvg));
    d1 = ((array2[i] * sl) + yi);
    squaredResidual = squaredResidual + ((array1[i] - d1) * (array1[i] - d1));
 }
 return 1 - (squaredResidual / squaredYVariance);
}
}

class runMyStats {
public static void main(String args[]) {
 double[] i2 = {5,10,20,8,4,6,12,15};
 double[] i = {27,46,73,40,30,28,46,59};
 //double[] i2 = {3,6,9,12};
 //double[] i = {15,30,45,60};
  myStats m = new myStats();
  System.out.println("AVG = " + m.average(i));
  System.out.println("STDEV = " + m.standardDeviation(i));
  System.out.println("Correlation = " + m.correlation(i,i2));
  System.out.println("Slope = " + m.slope(i,i2));
  System.out.println("YIntercept = " + m.yIntercept(i,i2));
  System.out.println("lineFit = " + m.lineFit(i,i2));
}
}