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
