def cochran(data, p=0.5):
mrgnerror = MarginOfError.marginoferror(data)
q = 1 - mrgnerror
z = ZScore.zscore(data)
return (Exponentiation.power(z, 2) * p * q) / Exponentiation.power(
mrgnerror, 2)
def SimpleSample(sd, data, rnge):
z = Zscore.zscore(data)
p = PopulationProportion.proportion(sd, data, rnge)
e = MarginError.margin(sd, data)
q = 1 - p
cochran = (Exponentiation.exponent(z, 2) * p *
q) / Exponentiation.exponent(e, 2)
return SimpleSample
def sample(list,p = 0.5,ci = 0.95):
e = Margin_Error.error(list,ci)
q = 1-p
z = Zscore.ZscoreCalculatorUsingAlpha(ci)
#print("Zvalue is ", z)
#print("error value is: ",e)
result = (Exponentiation.power(z,2)*p*q)/Exponentiation.power(e,2)
return result
def samplenostdev(data, p = 0.5):
zval = ZScore.zscore(data)
merror = MarginOfError.marginoferror(data)
q = 1 - p
pq = p*q
num = Exponentiation.power((zval/(merror/100)),2)*pq
return round(num, 2)
def SamplSizeCalc(cvalue, error, p=0.5):
zvalue = Zscore.ZscoreCalculatorUsingAlpha(cvalue)
#print("zvalue is ", zvalue)
q = 1 - p
pq = p * q
#print('pq value is ',pq)
temp = Exponentiation.power((zvalue / (error / 100)), 2) * pq
return round(temp, 2)
def sampleSize(sd, data):
e = MarginError.marginError(sd, data)
stdDev = StandardDeviation.standardDeviation(data)
val = (1.96 * stdDev) / e
sample = Exponentiation.exponent(val, 2)
return sample
def sampleSize(sd, data, percentage):
z = Zscore.zscore(sd, data)
e = MarginError.marginError(sd, data)
p = percentage
q = 1 - p
val = z/e
sample = Exponentiation.exponent(val, 2) * p * q
return sample
def deviation_Calculator(data):
newdata = []
data.sort()
n = len(data)
mean = Mean.Mean_Calculator(data)
for i in data:
newdata.append(Exponentiation.power((i - mean),2))
sum = Addition.sumList(newdata)
return nthRoot.rooting(2,Division.divide(sum,n))
def stardardDev(data):
n = len(data)
mn = Mean.mean(data)
newlist = []
for i in data:
newlist.append(Exponentiation.power(i - mn, 2))
total = Addition.sumList(newlist)
return nthroot.root(2, Division.divide(total, n))
def test_MathOperations_Exponentiation(self):
self.assertEqual(16, Exponentiation.power(4, 2))
def exponent(self, a, b):
self.Result = Exponentiation.exponent(a, b)
return self.Result
def variance(data):
return Exponentiation.power(StandardDeviation.stardardDev(data), 2)
def Power(self, a, b):
self.Result = Exponentiation.power(a, b)
return self.Result
def exponent(self, a, b):
self.result = Exponentiation.power(a, b)
return self.result
def samplestdev(data):
zval = ZScore.zscore(data)
stdDev = StandardDeviation.stardardDev(data)
merror = MarginOfError.marginoferror(data)
num = Exponentiation.power(((zval * stdDev) / (merror / 100)), 2)
return round(num, 2)
def test_MO_exp(self):
self.assertEqual(8, Exponentiation.power(2, 3))
def Variance_Calculator(data):
return Exponentiation.power(
Standard_Deviation.deviation_Calculator(data), 2)