def standard_deviation(data):
avg = mean(data)
num_values = len(data)
sd1 = 0
for num in data:
sd1 = addition(sd1, squared(subtraction(mean, num)))
return squarerooted(division(num_values, sd1))
def variance(val1, val2, val3, val4, val5, val6, val7, val8, val9, val10):
try:
variance_values = [
val1, val2, val3, val4, val5, val6, val7, val8, val9, val10
]
variance_float = [float(i) for i in variance_values]
variance_mean = mean(*variance_float)
variance_length = len(variance_float)
x = 0
for i in variance_float:
x = x + squared(i - variance_mean)
return division(x, subtraction(variance_length, 1))
except TypeError:
print("Median is a Number . Cannot Input Text")
def pvariance(val1, val2, val3, val4, val5, val6, val7, val8, val9, val10):
try:
pvariance_values = [
val1, val2, val3, val4, val5, val6, val7, val8, val9, val10
]
pvariance_float = [float(i) for i in pvariance_values]
pvariance_mean = mean(*pvariance_float)
pvariance_length = len(pvariance_float)
x = 0
for i in pvariance_float:
x = x + squared(i - pvariance_mean)
population_variance = division(x, pvariance_length)
return population_variance
except TypeError:
print("Population Variance is a Number . Cannot Input Text")
def square(self, a):
self.result = squared(a)
return self.result