Create ops subproject leveraging Apache Commons Math 3?

Nobody has claimed this yet.

Apache Commons Math 3 has lots of neat statistics functions. We should glance over them, and decide whether it makes sense to wrap any of them as ops. They all operate on `double[]` objects.

Here is an [example script](http://forum.imagej.net/t/coding-with-fiji/2089/8) from @BishopWolf:

``` python
from ij import IJ

from org.apache.commons.math3.stat.descriptive.rank import Min, Max, Median, Percentile
from org.apache.commons.math3.stat.descriptive.moment import Mean, Variance, Skewness, Kurtosis

imp = IJ.getImage()
ip = imp.getProcessor().convertToFloat() # as a copy
pixels = ip.getPixels()
newpixels = []

print "Image is", imp.title, "of type", imp.type

for pixel in pixels:
newpixels.append(pixel)

print "1. Minimum is:", Min().evaluate(newpixels)
print "2. Maximum is:", Max().evaluate(newpixels)
print "3. Median is:", Median().evaluate(newpixels)
print "4. Percentile is:", Percentile().evaluate(newpixels)
print "5. Mean is:", Mean().evaluate(newpixels)
print "6. Variance is:", Variance().evaluate(newpixels)
print "7. Skewness is:", Skewness().evaluate(newpixels)
print "8. Kurtosis is:", Kurtosis().evaluate(newpixels)
```

Start by reviewing the Apache Commons Math 3 descriptive statistics classes named in the issue and the linked example script. Determine which operations should be wrapped as ImageJ Ops and define the scope and acceptance criteria for the proposed subproject.

Written by the indexing model from the issue text.