How to Install and Uninstall ghc-statistics Package on openSuSE Tumbleweed

Last updated: December 25,2024

1. Install "ghc-statistics" package

This guide let you learn how to install ghc-statistics on openSuSE Tumbleweed


    
        
            $
        

        
            
                sudo zypper refresh
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo zypper install
            
                        
                ghc-statistics
            
                    
    
    Copied

2. Uninstall "ghc-statistics" package

Please follow the steps below to uninstall ghc-statistics on openSuSE Tumbleweed:


    
        
            $
        

        
            
                sudo zypper remove
            
                        
                ghc-statistics
            
                    
    
    Copied

3. Information about the ghc-statistics package on openSuSE Tumbleweed

Information for package ghc-statistics:
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Repository : openSUSE-Tumbleweed-Oss
Name : ghc-statistics
Version : 0.16.2.1-2.11
Arch : x86_64
Vendor : openSUSE
Installed Size : 4.2 MiB
Installed : No
Status : not installed
Source package : ghc-statistics-0.16.2.1-2.11.src
Upstream URL : https://hackage.haskell.org/package/statistics
Summary : A library of statistical types, data, and functions
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.