libstatistics-normality-perl 0.01-2 source package in Ubuntu
Changelog
libstatistics-normality-perl (0.01-2) unstable; urgency=medium
[ Salvatore Bonaccorso ]
* Update Vcs-* headers for switch to salsa.debian.org
[ gregor herrmann ]
* debian/watch: use uscan version 4.
[ Debian Janitor ]
* Bump debhelper from deprecated 9 to 12.
* Set debhelper-compat version in Build-Depends.
* Remove obsolete fields Contact, Name from debian/upstream/metadata (already
present in machine-readable debian/copyright).
* Bump debhelper from old 12 to 13.
-- Jelmer Vernooij <email address hidden> Fri, 17 Jun 2022 10:42:52 +0100
Upload details
- Uploaded by:
- Debian Perl Group
- Uploaded to:
- Sid
- Original maintainer:
- Debian Perl Group
- Architectures:
- all
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
| Series | Published | Component | Section | |
|---|---|---|---|---|
| Oracular | release | universe | misc | |
| Noble | release | universe | misc | |
| Mantic | release | universe | misc | |
| Lunar | release | universe | misc |
Downloads
| File | Size | SHA-256 Checksum |
|---|---|---|
| libstatistics-normality-perl_0.01-2.dsc | 2.2 KiB | d52f6a0ecd87c4ce4cc32853df17027e97be43631d36260b5783e00019650140 |
| libstatistics-normality-perl_0.01.orig.tar.gz | 9.7 KiB | 78283c792b738c8b17a056da928e366954659d8206109e7c05d26ec45b2df15c |
| libstatistics-normality-perl_0.01-2.debian.tar.xz | 2.5 KiB | da396061e6ff0926b487bc575d52204944ab89aa5122db1dc75aca080af06c64 |
Available diffs
- diff from 0.01-1.1 to 0.01-2 (1.1 KiB)
No changes file available.
Binary packages built by this source
- libstatistics-normality-perl: 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) distributed
population, especially because many downstream significance tests depend upon
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.
