def skew(set):
set = list((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
me = mean(set)
med = median(set)
std = sd(set)
sk = (3 * (me - med) / std)
return sk
def quartiles(data):
try:
List2 = []
num_values = len(data)
nNum = float(num_values)
Q2 = median(data)
nSort = sorted(data)
a = .25 * nNum
b = .75 * nNum
for num in nSort:
List2.append(num)
Q1 = List2[int(a)]
Q3 = List2[int(b)]
bb = addition(addition(int(Q1), int(Q2)), int(Q3))
return int(Q1), int(Q2), int(Q3)
except ZeroDivisionError:
print("Error - Cannot divide by 0")
except ValueError:
print("Error - Invalid data inputs")
def median(self, data):
self.result = median(data)
return self.result
def median(self):
self.result = median(self.data)
return self.result
def median(self, Value1, Value2, Value3, Value4, Value5, Value6, Value7,
Value8, Value9):
self.result = median(Value1, Value2, Value3, Value4, Value5, Value6,
Value7, Value8, Value9)
return self.result
def median(self, a, b, c):
self.result = median(a, b, c)
return self.result
def median(self):
self.result = median(self.median_list)
return self.result
def skewness(num):
mean_num = mean(num)
median_num = median(num)
stddev_num = stddev(num)
skew = ((mean_num - median_num) * 3) / stddev_num
return skew
def median(self, nums):
self.data = median(nums)
return self.data
def med(self, a):
self.result = median(a)
return self.result
def median(self, number_list):
self.result = median(number_list)
return self.result
def median(self, me):
self.result = median(me)
return self.result
def quartiles(data):
secondQuartile = median(data)
firstQuartile = numpy.percentile(data, 25)
thirdQuartile = numpy.percentile(data, 75)
return firstQuartile, secondQuartile, thirdQuartile
def stats_median(self, data):
self.result = median(data)
return self.result
def population_median(self, a):
self.result = median(a)
return self.result
def median(self, val1, val2, val3, val4, val5, val6, val7, val8, val9):
self.result = median(val1, val2, val3, val4, val5, val6, val7, val8,
val9)
return self.result
def median(self, data):
validate(data)
self.result = median(data)
return self.result
def median(self, data):
if is_valid(data):
self.result = median(data)
return self.result
else:
raise TypeError("Data contains non-numeric values")
