Incorrect first quantile and third quantile value over array using numpy

问题

I need help in understanding how the quantile function works in numpy. because the answers do not match with other quantile calculators.

arr = [1,2,3,4,5] 

print("arr : ", arr)  
print("Q2 quantile of arr : ", np.quantile(arr, .50)) 
print("Q1 quantile of arr : ", np.quantile(arr, .25)) 
print("Q3 quantile of arr : ", np.quantile(arr, .75))  

I expected the output of Q1 to be 1.5 and Q3 to be 4.5 I verified it using an online calculator. It also differs from the answer given by numpy . Can someone help me in understanding how numpy calculates quantile and why is it different from the actual formula .

回答1:

For some ungodly reason statistics as a discipline hasn't defined exactly what a quartile is, despite using it in many "standard" formulas. Here's three different methods of calculating it which which are all very different. Luckily when datasets are large the differences are small, but with only five values . . . well, you can get some very big differences.

• Your online calculator uses method 1 and returns [1.5, 4.5].

• The answer with method 2 would be [2, 4]

• numpy uses method 3 and returns [2, 4]

It seems to me like methods 2 and 3 would always give the same answer but there may be differences I haven't seen.

来源：https://stackoverflow.com/questions/57212996/incorrect-first-quantile-and-third-quantile-value-over-array-using-numpy