text: from Calculators.Calculator import Calculator
  from Statistics.Z_Score import z_score
  from Statistics.PopulationStandardDeviation import pop_stand_dev
  from Statistics.ConfidenceInterval import confidence_interval
  from Statistics.PopulationVariance import population_variance
  from Statistics.PopulationMean import population_mean
  from Statistics.Median import median
  from Statistics.Mode import mode
  from Statistics.VariancePopulationProportion import var_pop_proportion
  from Statistics.Proportion import proportion
  from Statistics.SampleVariance import var_sample_proportion
  from Statistics.SampleMean import sampleMean
  from Statistics.Pvalue import p_value
  from Statistics.SampleStandardDeviation import sample_st_dev
  from Statistics.PopulationCorrelationCoefficient import pop_correlation_coefficient
  from CSVReader.CSVReader import CsvReader
  
  class Statistics(Calculator):
      data = []
  
      def __init__(self):
          #self.data = CsvReader('Tests/Data/female_data.csv')
          super().__init__()
          pass
  
      def pop_mean(self, data):
          self.result = population_mean(data)
          return self.result
  
      def med(self, data):
          self.result = median(data)
          return self.result
  
      def mod(self, data):
          self.result = mode(data)
          return self.result
  
      def population_st_dev(self, data):
          self.result = pop_stand_dev(data)
          return self.result
  
      def variance_pop_proportion(self, data):
          self.result = var_pop_proportion(data)
          return self.result
  
      def z_score(self, data):
          self.result = z_score(data)
          return self.result
  
      def confidence_interval(self, data):
          self.result = confidence_interval(data)
          return self.result
  
      def population_variance(self, data):
          self.result = population_variance(data)
          return self.result
  
      def pop_correlation_coefficient(self, data_x, data_y):
          self.result = pop_correlation_coefficient(data_x, data_y)
          return self.result
  
      def proportion(self, data):
          self.result = proportion(data)
          return self.result
  
      def p_value(self, data):
          self.result = p_value(data)
          return self.result
  
      def sample_mean(self, data):
          self.result = sampleMean(data)
          return self.result
  
      def sample_st_dev(self, data):
          self.result = sample_st_dev(data)
          return self.result
  
      def var_sam_prop(self, data):
          self.result = var_sample_proportion(data)
          return self.result
  