Solution

• First, Generate a random number between 0 and 1 using a uniform distribution. This random number represents the outcome of a fair coin flip.
• Compare this random number with the probability of getting heads \(p\). If the random number is less than \(p\), you consider it as a head. Otherwise, it's a tail.

import numpy as np
def coin_toss(probability_of_head, number_of_trails):
    """
    Function to simulate coin toss
    Args:
    probability_of_head: this indicate whether coin is biassed or unbiassed
    number_of_trails: number of time experiment to be run
    Return:
    list which contains output of each trail
    """
    output_list = []
    if probability_of_head < 0 or probability_of_head > 1:
        return -1
    if number_of_trails < 0:
        return -1

    for i in range(number_of_trails):
        random_number = np.random.rand()
        if random_number<= probability_of_head:
            output_list.append(1)
        else:
            output_list.append(0)
    return output_list