sciPy stats.sem()函数| Python

scipy.stats.sem(arr, axis=0, ddof=0)函数用于计算输入数据平均值的标准误差。

Parameters :
arr : [array_like]Input array or object having the elements to calculate the standard error.
axis : Axis along which the mean is to be computed. By default axis = 0.
ddof : Degree of freedom correction for Standard Deviation.

Results : standard error of the mean of the input data.

例子：

# stats.sem() method 
import numpy as np
from scipy import stats
   
   
arr1 = [[20, 2, 7, 1, 34],
        [50, 12, 12, 34, 4]]
  
arr2 = [50, 12, 12, 34, 4]
  
print ("\narr1 : ", arr1)
print ("\narr2 : ", arr2)
  
print ("\nsem ratio for arr1 : ", 
       stats.sem(arr1, axis = 0, ddof = 0))
  
print ("\nsem ratio for arr1 : ", 
       stats.sem(arr1, axis = 1, ddof = 0))
  
print ("\nsem ratio for arr1 : ", 
       stats.sem(arr2, axis = 0, ddof = 0)) 

输出 ：

arr1 :  [[20, 2, 7, 1, 34], [50, 12, 12, 34, 4]]

arr2 :  [50, 12, 12, 34, 4]

sem ratio for arr1 :  [10.60660172  3.53553391  1.76776695 11.66726189 10.60660172]

sem ratio for arr1 :  [5.62423328 7.61892381]

sem ratio for arr1 :  7.618923808517841