How to Install and Uninstall ghc-statistics.x86_64 Package on Fedora 34
Last updated: November 25,2024
1. Install "ghc-statistics.x86_64" package
This is a short guide on how to install ghc-statistics.x86_64 on Fedora 34
$
sudo dnf update
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$
sudo dnf install
ghc-statistics.x86_64
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2. Uninstall "ghc-statistics.x86_64" package
Here is a brief guide to show you how to uninstall ghc-statistics.x86_64 on Fedora 34:
$
sudo dnf remove
ghc-statistics.x86_64
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$
sudo dnf autoremove
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3. Information about the ghc-statistics.x86_64 package on Fedora 34
Last metadata expiration check: 1:45:34 ago on Tue Sep 6 02:10:55 2022.
Available Packages
Name : ghc-statistics
Version : 0.15.2.0
Release : 7.fc34
Architecture : x86_64
Size : 723 k
Source : ghc-statistics-0.15.2.0-7.fc34.src.rpm
Repository : fedora
Summary : A library of statistical types, data, and functions
URL : https://hackage.haskell.org/package/statistics
License : BSD
Description : This library provides a number of common functions and types useful in
: statistics. We focus on high performance, numerical robustness, and use of good
: algorithms. Where possible, we provide references to the statistical
: literature.
:
: The library's facilities can be divided into four broad categories:
:
: * Working with widely used discrete and continuous probability distributions.
: (There are dozens of exotic distributions in use; we focus on the most common.)
:
: * Computing with sample data: quantile estimation, kernel density estimation,
: histograms, bootstrap methods, significance testing, and regression and
: autocorrelation analysis.
:
: * Random variate generation under several different distributions.
:
: * Common statistical tests for significant differences between samples.
Available Packages
Name : ghc-statistics
Version : 0.15.2.0
Release : 7.fc34
Architecture : x86_64
Size : 723 k
Source : ghc-statistics-0.15.2.0-7.fc34.src.rpm
Repository : fedora
Summary : A library of statistical types, data, and functions
URL : https://hackage.haskell.org/package/statistics
License : BSD
Description : This library provides a number of common functions and types useful in
: statistics. We focus on high performance, numerical robustness, and use of good
: algorithms. Where possible, we provide references to the statistical
: literature.
:
: The library's facilities can be divided into four broad categories:
:
: * Working with widely used discrete and continuous probability distributions.
: (There are dozens of exotic distributions in use; we focus on the most common.)
:
: * Computing with sample data: quantile estimation, kernel density estimation,
: histograms, bootstrap methods, significance testing, and regression and
: autocorrelation analysis.
:
: * Random variate generation under several different distributions.
:
: * Common statistical tests for significant differences between samples.