def zScore(numbers: list) -> list:
zScores = []
standardDeviation = DescriptiveStatisticsOperations.standardDeviation(numbers)
mean = DescriptiveStatisticsOperations.mean(numbers)
for number in numbers:
zScores.append(BasicOperations.division(BasicOperations.subtraction(number, mean), standardDeviation))
return zScores
def variance(numbers: list) -> float:
mean = DescriptiveStatisticsOperations.mean(numbers)
squaredDifferences = []
for number in numbers:
squaredDifferences.append(BasicOperations.square(BasicOperations.subtraction(mean, number)))
variance = BasicOperations.division(sum(squaredDifferences), len(numbers))
return variance
def median(numbers: list) -> float:
numbers = sorted(numbers)
if len(numbers) % 2 == 1:
middleIndex = int(BasicOperations.division(len(numbers) - 1, 2))
median = numbers[middleIndex]
else:
leftMiddleIndex = int(BasicOperations.subtraction(BasicOperations.division(len(numbers) - 1, 2), 0.5))
rightMiddleIndex = int(BasicOperations.addition(BasicOperations.division(len(numbers) - 1, 2), 0.5))
median = BasicOperations.division(BasicOperations.addition(numbers[leftMiddleIndex], numbers[rightMiddleIndex]), 2)
return float(median)
def subtract(self, x, y):
self.results.append(BasicOperations.subtraction(x, y))
return self.results[-1]