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gregoa pushed a commit to branch master
in repository libstatistics-normality-perl.
commit 231d95d467e6ed7082f0f7a58de2953e138af518
Author: gregor herrmann <gre...@debian.org>
Date: Wed Sep 14 18:47:04 2016 +0200
control
---
debian/control | 26 +++++++++++---------------
1 file changed, 11 insertions(+), 15 deletions(-)
diff --git a/debian/control b/debian/control
index da370be..a72513e 100644
--- a/debian/control
+++ b/debian/control
@@ -14,20 +14,16 @@ Testsuite: autopkgtest-pkg-perl
Package: libstatistics-normality-perl
Architecture: all
Depends: ${misc:Depends}, ${perl:Depends}
-Description: test whether an empirical distribution can be taken as being
drawn from a normally-distributed population
+Description: module for testing normal distribution of data
Various situations call for testing whether an empirical sample can be
- presumed to have been drawn from a normally
- (Gaussian|http://en.wikipedia.org/wiki/Normal_distribution) distributed
+ presumed to have been drawn from a normally (Gaussian) distributed
population, especially because many downstream significance tests depend upon
- the assumption of normality. This package implements some of the more
- well-known tests|http://en.wikipedia.org/wiki/Normality_test from the
- mathematical statistics literature, though there are also others that are not
- included. The tests here are all so-called omnibus tests that find departures
- from normality on the basis of skewness and/or kurtosis [Dagostino71]. Note
- that, although the Kolmogorov-Smirnov
- test|http://en.wikipedia.org/wiki/Kolmogorov%E2%80%93Smirnov_test can also be
- used in this capacity, it is a distance test and therefore not advisable
- [Dagostino71]. This, and other distance tests (e.g. Chi-square) are not
- implemented here.
- .
- This description was automagically extracted from the module by dh-make-perl.
+ the assumption of normality. Statistics::Normality implements some of the
+ more well-known normality tests from the mathematical statistics literature,
+ though there are also others that are not included. The tests here are all
+ so-called omnibus tests that find departures from normality on the basis of
+ skewness and/or kurtosis.
+ .
+ Note that, although the Kolmogorov-Smirnov test can also be used in this
+ capacity, it is a distance test and therefore not advisable. This, and other
+ distance tests (e.g. Chi-square) are not implemented here.
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