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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
)
(
"Trimmed Standard error:"
, stats.tsem (x))
(
"Trimmed Standard error by setting limit: "
,
stats. tsem (x, (
2
,
10
)))
Output:
Trimmed Standard error: 1.32287565553 Trimmed Standard error by setting limit: 0.912870929175Code # 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
(
"Trimmed Standard error is with default axis = 0:"
,
stats.tsem (arr1, axis
=
1
))
Exit:
Trimmed Standard error is with default axis = 0: 27.1476974115👻 Read also: what is the best laptop for engineering students?
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Olivia GalleottiSan Francisco | 2023-02-04
Simply put and clear. Thank you for sharing. sciPy function stats.tsem () | python and other issues with StackOverflow was always my weak point 😁. Will use it in my bachelor thesis
Olivia PorrettiPrague | 2023-02-04
Simply put and clear. Thank you for sharing. sciPy function stats.tsem () | python and other issues with io Python module was always my weak point 😁. I am just not quite sure it is the best method
Manuel GonzalezRome | 2023-02-04
Maybe there are another answers? What sciPy function stats.tsem () | python exactly means?. Will get back tomorrow with feedback