You need to calculate univariate statistics such as mean, median, variance, minimum and maximum.

Use Commons Math’s StatUtils to calculate simple univariate statistics. The following example uses StatUtils to calculate simple statistics for a double[]:

import org.apache.commons.math.stat.StatUtils;

double[] values = new double[] { 2.3, 5.4, 6.2, 7.3, 23.3 };

System.out.println( "min: " + StatUtils.min( values ) );
System.out.println( "max: " + StatUtils.max( values ) );
System.out.println( "mean: " + StatUtils.mean( values ) );
System.out.println( "product: " + StatUtils.product( values ) );
System.out.println( "sum: " + StatUtils.sum( values ) );
System.out.println( "variance: " + StatUtils.variance( values ) );

This code executes and prints a few simple statistics to the console, as follows:

min: 2.3
max: 23.3
mean: 8.9
product: 13097.61036
sum: 44.5
variance: 68.25500000000001

StatUtils delegates these calculations to functors in the org.apache.commons.math.stat.univariate.moment, org.apache.commons.math.stat.univariate.rank, and org.apache.commons.math.stat.univariate.summary packages. The following example uses the individual classes from these packages to recreate the previous example, and it adds some measures not available in StatUtil:

import org.apache.commons.math.stat.univariate.moment.*;
import org.apache.commons.math.stat.univariate.rank.*;
import org.apache.commons.math.stat.univariate.summary.*;

// Measures from previous example
Min min = new Min( );
Max max = new Max( );
Mean mean = new Mean( );
Product product = new Product( );
Sum sum = new Sum( );
Variance variance = new Variance( );

System.out.println( "min: " + min.evaluate( values ) );
System.out.println( "max: " + max.evaluate( values ) );
System.out.println( "mean: " + mean.evaluate( values ) );
System.out.println( "product: " + product.evaluate( values ) );
System.out.println( "sum: " + sum.evaluate( values ) );
System.out.println( "variance: " + variance.evaluate( values ) );
        
// New measures
Percentile percentile = new Percentile( );
GeometricMean geoMean = new GeometricMean( );
Skewness skewness = new Skewness( );
Kurtosis kurtosis = new Kurtosis( );

System.out.println( "80 percentile value: " + 
                    percentile.evaluate( values, 80.0 ) );
System.out.println( "geometric mean: " + geoMean.evaluate( values ) );
System.out.println( "skewness: " + skewness.evaluate( values ) );
System.out.println( "kurtosis: " + kurtosis.evaluate( values ) );

The previous example adds percentile, geometric mean, standard deviation, skewness, and kurtosis to the available univariate statistics. The previous example produces the following output:

min: 2.3
max: 23.3
mean: 8.9
product: 13097.61036
sum: 44.5
variance: 68.25500000000001
80 percentile value: 20.099999999999998
geometric mean: 6.659450778469037
standard dev: 8.261658429153314
skewness: 1.9446683453691376
kurtosis: 4.102348153299074

If you need a formal definition of a specific moment, rank, or summary, see MathWorld (http://mathworld.wolfram.com), an invaluable mathematical reference site from Wolfram, the makers of Mathematica.