How to Install and Uninstall perl-Statistics-ChiSquare.noarch Package on Oracle Linux 8

Last updated: May 16,2024

1. Install "perl-Statistics-ChiSquare.noarch" package

Please follow the guidance below to install perl-Statistics-ChiSquare.noarch on Oracle Linux 8


    
        
            $
        

        
            
                sudo dnf update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf install
            
                        
                perl-Statistics-ChiSquare.noarch
            
                    
    
    Copied

2. Uninstall "perl-Statistics-ChiSquare.noarch" package

This guide let you learn how to uninstall perl-Statistics-ChiSquare.noarch on Oracle Linux 8:


    
        
            $
        

        
            
                sudo dnf remove
            
                        
                perl-Statistics-ChiSquare.noarch
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo dnf autoremove
            
                    
    
    Copied

3. Information about the perl-Statistics-ChiSquare.noarch package on Oracle Linux 8

Last metadata expiration check: 7:07:58 ago on Mon Sep 12 02:51:38 2022.
Available Packages
Name : perl-Statistics-ChiSquare
Version : 1.0000
Release : 2.el8
Architecture : noarch
Size : 36 k
Source : perl-Statistics-ChiSquare-1.0000-2.el8.src.rpm
Repository : epel
Summary : How well-distributed is your data?
URL : https://metacpan.org/release/Statistics-ChiSquare
License : (GPLv2 or Artistic) and CC-BY-SA
Description : Suppose you flip a coin 100 times, and it turns up heads 70 times. Is the coin
: fair? Suppose you roll a die 100 times, and it shows 30 sixes. Is the die
: loaded?
:
: In statistics, the chi-square test calculates how well a series of numbers fits
: a distribution. In this module, we only test for whether results fit an even
: distribution. It doesn't simply say "yes" or "no". Instead, it gives you a
: confidence interval, which sets upper and lower bounds on the likelihood that
: the variation in your data is due to chance.