laplace_t_test.jl

using Distributions
using HypothesisTests

n_sims = 1_000_000
n = 2
x = Array{Float64}(n)
y = Array{Float64}(n)
p_d = Array{Float64}(n_sims)
for s in 1:n_sims
   for i in 1:n
       x[i] = rand(Laplace(0.0, 1.0))
       y[i] = rand(Laplace(0.0, 1.0))
   end
   try
       p_d[s] = pvalue(UnequalVarianceTTest(x, y))
   catch
       p_d[s] = NaN
   end
end
mean(isfinite.(p_d))
mean(p_d .< 0.05)
mean(p_d .< 0.01)
mean(p_d .< 0.001)

julia> mean(isfinite.(p_d))
1.0

julia> mean(p_d .< 0.05)
0.018487

julia> mean(p_d .< 0.01)
0.002538

julia> mean(p_d .< 0.001)
0.00019