def covariance(*stack):
items = checkParams(stack, 'plural')
X = average(items['Xi'])
Y = average(items['Yi'])
return items['XiYiFi']/items['Fi'] - X*Y
def variance(*items):
items = checkParams(items, 'single')
count = 0
count2 = 0
for item in items.keys():
count += item**2 * items[item]
count2 += items[item]
return count / count2 - average(items)**2
def average(*items):
items = checkParams(items, 'single')
X = 0
count = 0
for item in items.keys():
X += item * items[item]
count += items[item]
return X / count
def varianceB(*items):
items = checkParams(items, 'single')
count = 0
count2 = 0
mean = average(items)
for item in items.keys():
count += ((item - mean)**2)*items[item]
count2 += items[item]
return count / count2
def regressionLine(value, *stack):
items = checkParams(stack, 'plural')
value = {k.lower(): v for k,v in value.items()}
if 'x' in value:
diff = covariance(items)/varianceB(items['Xi'])
return diff*value['x']-diff*average(items['Xi'])+average(items['Yi'])
if 'y' in value:
diff = covariance(items)/varianceB(items['Yi'])
return diff*value['y']-diff*average(items['Yi'])+average(items['Xi'])
def correlationCoefficient(*stack):
items = checkParams(stack, 'plural')
return covariance(items)/(sqrt(varianceB(items['Xi']))*sqrt(varianceB(items['Yi'])))
def percentile(P, *items):
items = checkParams(items, 'single')
items = items.copy()
items, Fi = givePositions(items)
return getPosition(items, P*Fi/100)
def quartile(Q, *items):
items = checkParams(items, 'single')
items = items.copy()
items, Fi = givePositions(items)
return getPosition(items, Q*Fi/4)
def median(*items):
items = checkParams(items, 'single')
items = items.copy()
items, Fi = givePositions(items)
return getPosition(items, Fi/2)