Generating many bootstrap replicates
The function bootstrap_replicate_1d() from the video is available in your namespace. Now you'll write another function, draw_bs_reps(data, func, size=1), which generates many bootstrap replicates from the data set. This function will come in handy for you again and again as you compute confidence intervals and later when you do hypothesis tests.
For your reference, the bootstrap_replicate_1d() function is provided below:
def bootstrap_replicate_1d(data, func):
return func(np.random.choice(data, size=len(data)))
This exercise is part of the course
Statistical Thinking in Python (Part 2)
Exercise instructions
- Define a function with call signature
draw_bs_reps(data, func, size=1).- Initialize an array,
bs_replicatesto hold all of the bootstrap replicates usingnp.empty(). - Write a
forloop to compute a replicate usingbootstrap_replicate_1d()and stores the replicate inbs_replicates. - Return the array of replicates.
- Initialize an array,
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
def draw_bs_reps(data, func, size=1):
"""Draw bootstrap replicates."""
# Initialize array of replicates: bs_replicates
bs_replicates = ____
# Generate replicates
for i in ____:
bs_replicates[i] = ____
return bs_replicates