Simple permutation testing code from http://spark.rstudio.com/ahmed/permutation/ (used to show the same effect as the more complex code: https://gist.github.com/Sarkom/95e3c7ecfcdbddeec959)

simple_permutation_test.R

# Copy of code from http://spark.rstudio.com/ahmed/permutation/

a  = rnorm(1000, 0, 1)
b  = rnorm(1000, 100, 1.5)

# Combine the two datasets into a single dataset
# i.e., under the null hypothesis, there is no difference between the two groups
combined = c(a,b)

# Observed difference
diff.observed = var(b) - var(a)

number_of_permutations = 1000

diff.random = NULL
for (i in 1 : number_of_permutations) {
  
  # Sample from the combined dataset without replacement
  shuffled = sample (combined, length(combined))
  
  a.random = shuffled[1 : length(a)]
  b.random = shuffled[(length(a) + 1) : length(combined)]
  
  # Null (permuated) difference
  diff.random[i] = var(b.random) - var(a.random)
}

# P-value is the fraction of how many times the permuted difference is equal or more extreme than the observed difference

pvalue = sum(abs(diff.random) >= abs(diff.observed)) / number_of_permutations
print (pvalue)


# Combine the two datasets into a single dataset
# i.e., under the null hypothesis, there is no difference between the two groups
combined = c(a,b)

# Observed difference
diff.observed = sd(b) - sd(a)

number_of_permutations = 1000

diff.random = NULL
for (i in 1 : number_of_permutations) {
  
  # Sample from the combined dataset without replacement
  shuffled = sample (combined, length(combined))
  
  a.random = shuffled[1 : length(a)]
  b.random = shuffled[(length(a) + 1) : length(combined)]
  
  # Null (permuated) difference
  diff.random[i] = sd(b.random) - sd(a.random)
}

# P-value is the fraction of how many times the permuted difference is equal or more extreme than the observed difference

pvalue = sum(abs(diff.random) >= abs(diff.observed)) / number_of_permutations
print (pvalue)