Exercise

# 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):
"""Generate bootstrap replicate of 1D data."""
bs_sample = np.random.choice(data, len(data))
return func(bs_sample)
```

Instructions

**100 XP**

- Define a function with call signature
`draw_bs_reps(data, func, size=1)`

.- Using
`np.empty()`

, initialize an array called`bs_replicates`

of size`size`

to hold all of the bootstrap replicates. - Write a
`for`

loop that ranges over`size`

and computes a replicate using`bootstrap_replicate_1d()`

. Refer to the exercise description above to see the function signature of`bootstrap_replicate_1d()`

. Store the replicate in the appropriate index of`bs_replicates`

. - Return the array of replicates
`bs_replicates`

. This has already been done for you.

- Using