INNER CODE UNIT · Python
like_insta_post
tuangauss/DataScienceProjects · Python/lincoln_estimate.py:3
def like_insta_post(p):
"Find an error with probability p"
return 1 if random.random() < p else 0
def simulate(true_audience, p1, p2, reps=10000):
"""Simulate Lincoln's method for estimating errors
given the true number of errors, each person's probability
of finding an error, and the number of simulations to run."""
naive_estimates = []
lincoln_estimates = []
for rep in range(reps):
like_post_1 = np.array([like_insta_post(p1) for _ in range(true_audience)])
like_post_2 = np.array([like_insta_post(p2) for _ in range(true_audience)])
like_post1_count = sum(like_post_1)
like_post2_count = sum(like_post_2)
overlap = np.sum(like_post_1 & like_post_2)