**Bootstrapping** is a procedure similar to jackknifing. The basic bootstrapping method has the following steps:

- Generate samples from the original data of size
*N.*Visualize the original data sample as a bowl of numbers. We create new samples by taking numbers at random from the bowl. After taking a number, we return it to the bowl. - For each generated sample, we compute the statistical estimator of interest (for example, the arithmetic mean).

We will apply `numpy.random.choice()`

to do bootstrapping:

- Generate a data sample following the binomial distribution that simulates flipping a fair coin five times:
N = 400 np.random.seed(28) data = np.random.binomial(5, .5, size=N)

- Generate 30 samples and compute ...

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