Bootstrap Mean

Estimate a percentile bootstrap confidence interval for the mean of a sample. Draw B resamples of the same size with replacement using np.random.default_rng(seed), take each resample's mean, and return the alpha/2 and 1 - alpha/2 quantiles of those means.

Implement solve(x, B=1000, alpha=0.05, seed=0).

Returns. Return a tuple (low, high) of Python floats. Quantiles use NumPy's default linear interpolation.

Examples

Example 1

Input:

solve([1.0, 2.0, 3.0, 4.0])

Output:

(1.5, 3.5)

Example 2

Input:

solve([5.0, 5.0, 5.0])

Output:

(5.0, 5.0)

Example 3

Input:

solve([1.0, 2.0, 3.0, 4.0, 10.0], B=500, alpha=0.1, seed=7)

Output:

(2.0, 6.8)