sciPy function stats.tsem () | python

NumPy | Python Methods and Functions

Its formula: —

Parameters:
array: Input array or object having the elements to calculate the trimmed standard error of the mean .
axis: Axis along which the trimmed standard error of the mean is to be computed. By default axis = 0.
limits: Lower and upper bound of the array to consider, values ​​less than the lower limit or greater than the upper limit will be ignored. If limits is None [default], then all values ​​are used.

Returns: Trimmed standard error of the mean of array elements based on the set parameters.

Code # 1:

# Cropped standard error

 

from scipy import stats

import numpy as np 

 
# array elements in the range from 0 to 19

x = np.arange ( 20 )

 

< code class = "functions"> print ( "Trimmed Standard error:" , stats.tsem (x)) 

 

 

print ( "Trimmed Standard error by setting limit: "

  stats. tsem (x, ( 2 , 10 )))

Output:

 Trimmed Standard error: 1.32287565553 Trimmed Standard error by setting limit: 0.912870929175 

Code # 2: with multidimensional data, the () axis works

 # Cropped standard error

 

from scipy import stats

import numpy as np 

  

arr1 = [[ 1 , 3 , 27 ], 

[ 5 , 3 , 18 ], 

[ 17  , 16 , 333 ], 

  [ 3 , 6 , 82 ]] 

 

 
# using axis = 0

print ( "Trimmed Standard error is with default axis = 0:"

stats.tsem (arr1, axis = 1 ))

Exit:

 Trimmed Standard error is with default axis = 0: 27.1476974115 




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