How can I efficiently calculate the binomial cumulative distribution function?

Question

Let\'s say that I know the probability of a \"success\" is P. I run the test N times, and I see S successes. The test is akin to tossing an unevenly weighted coin (perhaps

Answer 1

import numpy as np
np.random.seed(1)
x=np.random.binomial(20,0.6,10000) #20 flips of coin,probability of 
                                 heads percentage and 10000 times 
                                  done.
sum(x>12)/len(x)

The output is 41% of times we got 12 heads.