Suppose a random variable X has a uniform distribution on the integers {0, 1, ..., 9}(i.e., P[X = k] = 1/10 for k = 0, 1, ..., 9). Estimate E[X], Var [X], and E[f (X)] Where f(x) = x^3using Monte Carlo simulation in Python. In particular generate N Monte Carlo samples x_1, x_2, .., x_N for X. Then, calculate the estimate E[f(x)] 1/N sigma_n =1^N f(x_n). Use N = 10,000 Monte Carlo samples To generate samples of a discrete uniform random variable in Python: import numpy as np N = 10000 for i in range (N): U = np. random randint(0, 10) Suppose a random variable X has a uniform distribution on the integers {0, 1, ..., 9}(i.e., P[X = k] = 1/10 for k = 0, 1, ..., 9). Estimate E[X], Var [X], and E[f (X)] Where f(x) = x^3using Monte Carlo simulation in Python. In particular generate N Monte Carlo samples x_1, x_2, .., x_N for X. Then, calculate the estimate E[f(x)] 1/N sigma_n =1^N f(x_n). Use N = 10,000 Monte Carlo samples To generate samples of a discrete uniform random variable in Python: import numpy as np N = 10000 for i in range (N): U = np. random randint(0, 10)