# import statistics library as stat # import statistics as stat # # import matplotlib.pyplot as plt and NumPy as np import matplotlib.pyplot as plt import numpy as np list = [6, 8, 12, 14] stat.stdev ( list)

temps = [45, 51, 38, 42, 47, 51, 52, 55, 48, 43] n = len(temps) # for plotting purposes I have added an array of days from 1 to 10 days = np.linspace(1,n,n) temps_array = np.array (temps) print (stat.mean (temps_array)) print (stat.median ( temps_array)) print (stat.mode (temps_array )) print (stat.variance(temps_array)) print (format (stat.stdev(temps_array), ".3f"))

temps = [45, 51, 38, 42, 47, 51, 52, 55, 48, 43] n = len(temps) days = np.linspace(1,n,n) x_axis = days y_temp = temps_array mean = (stat.mean (temps_array)) y_mean = ((np.ones (len (temps)))* mean) sdev = (format (stat.stdev(temps_array), ".3f")) plt.plot (x_axis, y_temp, "rx") plt.plot (x_axis, y_mean, "g")

y_sdev = ((np.ones (len (temps)))* sdev) y_SD = np.array ((format (stat.stdev(temps_array), ".3f"))* (np.ones (len (temps)))) plt.plot (x_axis, y_SD, "--b")

# Plot the temperatures vs the days as a scatter plot using a red "x" # # Plot the mean as a horizontal line in green # # Illustrate 1 standard deviation away from the mean by drawing two horizonal lines in # as dotted blue lines plt.show()

import random n = 15 for x in range (0, n): print (random.randint(100, 200))

import numpy as np print (np.random.randint (low= 100, high= 200, size= 15))

n = 15 for x in range (0,n): print (random.random ())

print (np.random.uniform (size= 15))

for i in range (0, 16): x = random.random () y = 10 + 30 * x print (y)

x = np.random.uniform (size= 15) y = 10 + 30 * x print (y)

x = np.random.normal (size= 15) print (x)

y = 20 + x*(0.5) print (y)