In [27]:

    

using Distributions
using PyPlot


    

In [5]:

    

function middle()
    xs = rand(Uniform(0, 1), 2)
    abs(xs[1] - xs[2])
end


    

    
Out[5]:





middle (generic function with 1 method)

In [45]:

    

n = 1000000
xs = [abs(rand(Uniform(0, 1)) - rand(Uniform(0, 1))) for i in 1:n]
nbins = 50
plt[:hist](xs, nbins)
mean(xs)


    

    













    
Out[45]:





0.333286143680113