def samplestand(data, sample_size): dev = 0 sample = sampledata(data, sample_size) sample_values = len(sample) x_bar = mean() x = sample_values n = subtraction(sample_values, 1) for dev in sample: dev = subtraction(x, x_bar) square_x_bar = square(dev) add = addition(square_x_bar, square_x_bar) result = division(add, n) return squareroot(result)
def zscore(data): x=64 u=mean(data) sample_sd=samplestand(data) y=subtraction(x,u) return division(sample_sd,y)
def standardised_score(my_pop): my_mean = mean(my_pop) my_sd = popstand(my_pop) standardised_score = float(list()) for x in my_pop: my_score = (x - my_mean) / my_sd standardised_score.append(my_score) return standardised_score
def StdDevSample(data): Sum1 = 0 for i in data: x = abs(i - mean(data)) Sum1 = square(x) + Sum1 n = len(data) stdDev = math.sqrt(Sum1 / (n - 1)) return stdDev
def StdDevPop(data): Sum2 = 0 for i in data: x = abs(i - mean(data)) Sum2 = square(x) + Sum2 n = len(data) stdDev = math.sqrt(Sum2) / n return stdDev
def popuvar(numbers): num_value = len(numbers) total = 0 for numb in numbers: result = subtraction(numb, mean(numb)) result1 = square(result) result2 = division(num_value, result1) return result2
def vpop(numbers): num_values = len(numbers) result = mean(numbers) total = 0 for numb in numbers: result2 = subtraction(numb, result) sq = square(result2) total = addition(total, sq) return division(num_values, total)
def mean(self): d = [] for row in self.data.data: d.append(row['v']) self.result = mean(d) return self.result
def mean(self, data): self.result = mean(data) return self.result