import numpy as np

import matplotlib.pyplot as plt

from scipy.stats import norm

from scipy.stats import expon

from scipy.stats import binom

from scipy.stats import poisson

# creates a uniform set of 100000 values from -10 to 10

values = np.random.uniform(-10, 10, 100000)

plt.hist(values, 50)

plt.show()

# creates a range from -3 to 3 in increments of 0.001

x = np.arange(-3, 3, 0.001)

# plots a graph of the probability density function

plt.plot(x, norm.pdf(x))

mu = 5

sigma = 2

values = np.random.normal(mu, sigma, 10000)

plt.hist(values, 50)

plt.show()

# creates exponential probability density function

x= np.arange(0, 10, 0.001)

plt.plot(x, expon.pdf(x))

# creates binomial probability mass function

n, p = 10, 0.5

x= np.arange(0, 10, 0.001)

plt.plot(x, binom.pmf(x, n, p))

# creates poisson probability mass function

# gets the odds of 500 NOT happening

mu = 500

x = np.arange(400, 600, 0.5)

plt.plot(x, poisson.pmf(x, mu))