text: 
  
  class Stats:
      """ Class of basic statistics methods implemented without numpy. """
      def __init__(self, numbers):
          self.numbers=numbers
  
      def mean(self):
          return sum(self.numbers)/len(self.numbers)
  
      def median(self):
          """ Calculates median by first finding the midpoint depending on
              whether the self.numbers is even- or odd-length. """
          if len(self.numbers) % 2 == 0:
              halfway = len(self.numbers) / 2
              return sum(sorted(self.numbers)[int(halfway) - 1 : int(halfway) + 1]) / 2
          else:
              halfway = len(self.numbers) // 2
              return sorted(self.numbers)[halfway]
  
      def mode(self):
          highest = 0
          mode = 0
          no_mode = True
          for i in set(self.numbers):
              counted = self.numbers.count(i)
              if counted > highest:
                  highest = counted
                  mode = i
                  no_mode = False
              elif counted == highest and i != mode:
                  no_mode = True
          if no_mode == False:
              return mode
          elif no_mode == True:
              return None
  
      def variance(self):
          sample_mean = self.mean()
          squared_deviations = []
          for i in self.numbers:
              deviation = i - sample_mean
              squared_deviations.append(deviation**2)
          sse = sum(squared_deviations)
          return sse / (len(self.numbers) - 1)
  
      def std(self):
          return self.variance()**0.5
  
      def coef_var(self):
          return self.std() / self.mean()
  