Obtaining GNU PSPP

1. PSPP is a powerful and versatile utility designed as a free alternative for the proprietary program SPSS and, as a result, it provides numerous tools and features that can help you in the statistical analysis of sampled data. Open source IBM SPSS alternative for macOS. First of all, if you download the.
2. PSPP is a software for performing statistical analysis of data samples based on SPSS. The possibilities of the application include: supporting 1 billion of variables and values; syntax and data files compatible with SPSS; export of data to pdf, txt, odt, ps or html formats; sorting and searching by cases.

PSPP is GNU software. You can obtain it the same way as with anyGNU software. PSPP should work on most modern computers and most operatingsystems. Systems which have been known to work include:GNU/Hurd,GNU/Linux,Darwin (Mac OS X), OpenBSD,NetBSD, FreeBSD, and Windows.

The selected gretl package file should appear in your Downloads after a short while, or it may be opened by the Mac Installer program right away. If the package is not opened automatically, minimize your browser window so you can see what's happening on your desktop, then double-click on the gretl file in Downloads to open the installer. CNET Download provides free downloads for Windows, Mac, iOS and Android devices across all categories of software and apps, including security, utilities, games, video and browsers.

Binaries

GNU Linux

We do not distribute precompiled binaries of PSPP. Computers come with so many different archtectures, kernels, operating systems that it would not be feasible for us to do so. However most modern operating systems come with PSPP pre-packaged. To install it, you simply type apt-get install pspp in the case of Debian derived systems; or yum install pspp in the case of Red Hat derived systems.

Windows

Harry Thijssen provides installers or all downloadable files. The windows version is build as cross compile build on openSUSE. There is also a nightly build with development versions.

MacOS

There are three ways to install PSPP on MacOS.

• The Application bundle provides the gui version via a normal installer. If you do not know what XCode is - go for this one.
• MacPorts. Run port install pspp-devel to get the latest and most featureful version of PSPP or port install pspp to get an older but possibly better tested version (more information).
• Homebrew. The PSPP brew tap also includes a description how to install the stable or the development version of PSPP.

Please note: Because the PSPP developers have not prepared these binaries, we cannot in general vouch for them.

Source

If you want to compile and install PSPP yourself, you can get the source code fromhttp://ftpmirror.gnu.org/pspp.Should this link be unavailable or unreasonably slow, please select a local mirror site.Once you have downloaded the tarball, refer to the INSTALLfile for installation instructions.

Development Versions

PSPP is under continual improvement. You can get development versions if you are interested to see what the developers are working on. Development versions have undergone less testing than released versions.

You can fetch the latest development sources fromthe Savannah GITrepository.The installationprocedure is more complex than for released versions, so werecommend this only for developers.

Automated builds of the developmentversions are performed typically every day.

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Data Visualization Lab Videos

Title

Intro to Statistical Tools: R vs. PSPP

Files

Download R-v-PSPP Quiz Solutions.pdf (44 KB)

Download RvPSPP_Workshop-RstudioScript.R (668 B)

Description

A simple example of hypothesis testing using R vs. PSPP – a free alternative to SPSS! See comments for download links, sample question and quiz.

Publication Date

Spring 2020

City

New Orleans, LA

Disciplines

Online and Distance Education | Statistics and Probability

Recommended Citation

Pspp Statistical Software Download Mac Installer

Saltzman, Alex, 'Intro to Statistical Tools: R vs. PSPP' (2020). Data Visualization Lab Videos. 13.
https://digitalcommons.xula.edu/data_instruct/13

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