text: import numpy as np
  import matplotlib.pyplot as plt
  import scipy.stats as sp
  import math
  import random as rm
  import NumerosGenerados as ng
  from Tests import testNormal
  
  n = 1000000
  esperanza = 0
  desvio = 20
  numerosNormal = sp.norm.rvs(size=n, loc = esperanza, scale=desvio)
  
  print("Media: ", round(np.mean(numerosNormal),3))
  print("Desvio: ", round(np.sqrt(np.var(numerosNormal)),3))
  print("Varianza: ", round(np.var(numerosNormal),3))
  
  plt.hist(numerosNormal, bins=50, color='red', histtype="bar",alpha=0.8,ec="black")
  plt.xlabel("valores")
  plt.ylabel("Frecuencia Absoluta")
  plt.show()
  
  #----------Naylor----------
  randomGCL = ng.generarNumeros(n*12)
  
  normales = []
  
  def normal(esperanza, desvio):
      for i in range (n):
          sumatoria = 0
          for j in range (12):
              r=rm.choice(randomGCL)
              sumatoria = sumatoria + r
          normales.append((desvio * (sumatoria-6)) + esperanza )
      print("Media: ", round(np.mean(normales),3))
      print("Desvio: ", round(np.sqrt(np.var(normales)),3))
      print("Varianza: ", round(np.var(normales),3))
      plt.title("Distribuciones Normales")
      plt.hist(numerosNormal, bins=50, color='red', histtype="bar",alpha=0.8,ec="black")
      plt.hist(normales, bins=50,color = 'skyblue', histtype="bar",alpha=0.8,ec="black")
      plt.show()
  
  normal(esperanza,desvio)
  
  testNormal(normales,esperanza,desvio)