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Generating permutation replicates

As discussed in the video, a permutation replicate is a single value of a statistic computed from a permutation sample. As the draw_bs_reps() function you wrote in chapter 2 is useful for you to generate bootstrap replicates, it is useful to have a similar function, draw_perm_reps(), to generate permutation replicates. You will write this useful function in this exercise.

The function has call signature draw_perm_reps(data_1, data_2, func, size=1). Importantly, func must be a function that takes two arrays as arguments. In most circumstances, func will be a function you write yourself.

This exercise is part of the course

Statistical Thinking in Python (Part 2)

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Exercise instructions

  • Define a function with this signature: draw_perm_reps(data_1, data_2, func, size=1).
    • Initialize an array to hold the permutation replicates using np.empty().
    • Write a for loop to:
      • Compute a permutation sample using your permutation_sample() function
      • Pass the samples into func() to compute the replicate and store the result in your array of replicates.
    • Return the array of replicates.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

def draw_perm_reps(data_1, data_2, func, size=1):
    """Generate multiple permutation replicates."""

    # Initialize array of replicates: perm_replicates
    perm_replicates = ____

    for i in ____:
        # Generate permutation sample
        perm_sample_1, perm_sample_2 = ____

        # Compute the test statistic
        perm_replicates[i] = ____

    return perm_replicates
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