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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Computing Mean, Variance, Higher Moments, and Their Linear Combinations under Interval Uncertainty: A Brief Summary
verfasst von : Hung T. Nguyen, Vladik Kreinovich, Berlin Wu, Gang Xiang
Erschienen in: Computing Statistics under Interval and Fuzzy Uncertainty
Verlag: Springer Berlin Heidelberg
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In the previous chapters, we described several results and algorithms for computing:
the mean
E
,
the variance
V
=
σ
2
=
$\frac{1}{n}$
·
$\sum\limits^{n}_{i=1}{(x_{i} - E)}^{2}$
,
more generally, higher central moments
M
h
=
$\frac{1}{n}$
·
$\sum\limits^{n}_{i=1}{(x_{i} - E)}^{h}$
and
statistically useful linear combinations of these characteristics – such as the lower and upper endpoints of the confidence interval
L
=
E
–
k
0
·
σ
and
U
=
E
+
k
0
·
σ
, where the parameter
k
0
is usually taken as
k
0
= 2,
k
0
= 3, and
k
0
= 6.