Michael Grogan MGCodesandStats

## marketsegment.csv

          
            MarketSegment
             Average - ADR

            
              Complementary
              	3.65

            
              Corporate
              	51.56

            
              Direct
               111.67

            
              Groups
              	66.44

            
              Offline TA/TO
              	74.66

            
              Online TA
              	113.43

            
              Total Result
              	94.95

## binomial_class_polymorphism
class Binomial(Probability):
    def __init__(self, length):
        super().__init__("Binomial")
        self.length = length

    def binomial5(self):
        return np.sum((np.random.binomial(9, 0.05, self.length) == 0))/self.length

    def binomial10(self):
        return np.sum((np.random.binomial(9, 0.1, self.length) == 0))/self.length

## pareto_class_polymorphism
class Pareto(Probability):
    def __init__(self, length):
        super().__init__("Pareto")
        self.length = length

    def mode1(self):
        return (np.random.pareto(3, self.length) + 1) * 1

    def mode2(self):
        return (np.random.pareto(3, self.length) + 1) * 2
	MarketSegment	Average - ADR
	Complementary	3.65
	Corporate	51.56
	Direct	111.67
	Groups	66.44
	Offline TA/TO	74.66
	Online TA	113.43
	Total Result	94.95
	class Binomial(Probability):
	def __init__(self, length):
	super().__init__("Binomial")
	self.length = length

	def binomial5(self):
	return np.sum((np.random.binomial(9, 0.05, self.length) == 0))/self.length

	def binomial10(self):
	return np.sum((np.random.binomial(9, 0.1, self.length) == 0))/self.length
	class Pareto(Probability):
	def __init__(self, length):
	super().__init__("Pareto")
	self.length = length

	def mode1(self):
	return (np.random.pareto(3, self.length) + 1) * 1

	def mode2(self):
	return (np.random.pareto(3, self.length) + 1) * 2