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GNU PSPP — Frequently Asked Questions

Here we try to answer some of the questions about PSPP that arise from time to time.

What is PSPP?

PSPP is a program for statistical analysis of sampled data. Itis a free replacement for the proprietary program, SPSS.

One goal of the PSPP project is compatibility with the SPSSlanguage. It currently features:

Monte Carlo PCA for Parallel Analysis computes Parallel Analysis criteria (eigenvalues) for determining the number of factors to retain for rotation in factor analysis. Join over 500,000 subscribers. Subscribe for our newsletter with best Mac offers from MacUpdate. JMetrik is a free software application for psychometric analysis. It includes procedures for basic desciptive statistics, graphs, classical item analysis, factor analysis, and item response theory. JMetrik is a pure Java application that runs on Windows, Mac OSX, and Linux platforms. The jMetrik graphical user interface (GUI) combines a workspace tree, data view, point-and-click menu,. Oct 09, 2017 PSPP is a free statistical anaylsis software for Mac for analysis of sampled data. PSPP is similar to a free version of SPSS which we covered in our in-depth look at the best statistical software for Mac. However, PSPP is aimed more at statisticians, social scientists and students that need quick analysis of sampled data. What is Factor Analysis. Exploratory factor analysis (or EFA) is a method that reveals the possible existence of underlying factors which give an overview of the information contained in a very large number of measured variables. The structure linking factors to variables is initially unknown and only the number of factors may be assumed. Something doesn't work properly on Windows/Mac. PSPP is a program for statistical analysis of sampled data. It is a free replacement for the proprietary program, SPSS. One goal of the PSPP project is compatibility with the SPSS language. It currently features: High-quality output formatting.

  • High-quality output formatting.
  • An easy to use graphical user interface.
  • A command line interface to allow seasoned users to rapidly perform analysis.
  • A comprehensive selection of data preprocessing, analysis and visualisation commands.
  • Portability: PSPP can be built on a very wide range of platforms.

What can PSPP do?

PSPP provides many transformations and utilities. Procedures provide the ability to perform t-tests, anova, linear regression,logistic regression, cluster analysis,reliability analysis, factor analysis, non parametric tests and other analyses.

Refer to the manual for the completelist of supported commands.

Where can I get PSPP?

See this page.

How do I install PSPP?

There are several methods:

  • Many operating systems come with PSPP already packaged. This is often the easiest method, but might not get you the most up to date version. An incomplete list of packages for various operating systems.
  • Download a tarball and follow the instructions in theINSTALL file.This is the canonical method used for most GNU software.
  • However, if really want the very latest version, and are willing to put in extra effort to install it, and are prepared to accept that it may contain bugs, then compile from the Git snapshot. Look in the fileREADME.GIT file and follow the instructions there.

How do I get started using PSPP?

Having installed PSPP, try this:

  1. Using your favourite editor, write a file (name it myfile.sps) containing the following:
  2. Enter the command pspp myfile.sps
  3. Look at your results in pspp.list

PSPP is very versatile and there are lots of different types ofstatistical analysis possible. You need to become familiar with thedocumentation to unleash its full potential.

How do I configure the PSPP interface language?

PSPP respects the locale of the environment. So if, for example, youroperating system (or the currently logged in user) is set toPortuguese, then that is what PSPP will display.

How you change the environment's locale depends on the operatingsystem. For example, on GNU or on GNU/Linux you could use the commandexport LANG=pt_PT (for Portuguese spoken in Portugal)or export LANG=pt_BR for Brazillian Portuguese. Thisshould also work for all operating systems which are POSIX compliant.For others, you will have to refer to your OS documentation.

What documentation is available?

The PSPP manual,written in Texinfo format, is the primary reference for using PSPP.Besides the Texinfo format a few other formats are available like HTML and PDF. A fewadditional documentation files are included in the source distribution:

A quick introduction to PSPP.
Notes on building and installing.
Details of the latest bleeding edge changes.

A manual for PSPP in French, written independently by Julie Séguéla, is alsoavailable in PDFand LaTeXformats.

A guide to PSPP in Polish, written independently by Daniel Mider and AnetaMarcinkowska, is also available.

There are also heaps of unofficial resources on the internet.Use a search engine to find them.

There are a lot of concepts I don't understand. Where can I learn about them?

One good online introductory statistics textbook isOnline Statistics Education: A Multimedia Course of Study (http://onlinestatbook.com/). Project Leader: David M. Lane, Rice University.Disclaimer: PSPP, its developers and the GNU Project have no affiliation with this publisher or author of this book.

PSPP is a clone of SPSS. So why should I use PSPP when SPSS has all the same features?

Firstly, PSPP is not a 'clone'. No part of SPSS was used to write PSPP and there is no code shared between the projects. If it was a clone, then therewould indeed be no advantage using one program or the other.But instead, PSPP is an independent free software program (and one of its design goals was ease of use for people already familiar with SPSS).

Among other advantages, this means that if you find it doesn't completelyfit your needs - perhaps there is a statistical test which you would like itto perform - then you have the means and the right to improve it to fit your requirements. Whereas if you attempted to do this with non-free software such as SPSS it would be both difficult and illegal.


Furthermore, because PSPP is free software, you can use it for whatever you like and for as long as you like (there's no 'expiry') and you are welcome to give away (or sell) copies to others - for example to students undertaking anintroductory statistics course. If you have made your own improvements, then you can include those changes in the copies you distribute.

Another important advantage: Since the source code is available to all, unlimited peer review is possible. Should PSPP's accuracy be called intoquestion, it can easily be audited by a competent, independent authority.Conversely, since the source code of proprietary software is secret, nobodycan check to see if it contains numerical instability, inappropriate algorithm implementations or other potential errors.

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Some secondary reasons why people sometimes prefer PSPP include:

  • Reduced costs
  • Inter platform portability
  • A number of people have reported that PSPP runs faster
  • Features not available in other software, such as importing from Postgres, Gnumeric etc.
  • It comes already bundled with popular operating systems, such as Debian GNU/Linux

How can I be sure that PSPP gives accurate results?

When you install PSPP, the GNU Project gives you exactly the same warranty that you would get with any proprietary program viz:None at all.

However, we feel confident that PSPP provides reliable and accurate results for a number or reasons

  • Every release has over 1000 tests. These are run before each release. In addition, you can run them on your own machine to make sure PSPP is accurate for your platform.
  • For many years there has been a publicly available bug reporting and tracking service, where anyone can report problems. Many issues have been brought to our attention but there have been few, if any, confirmed reports of a miscalculated statistic on a released PSPP version.
  • We regularly analyse the code using tools such as valgrind and gcov to expose any latent defects.
  • The complete source code is available for everyone to review which, should bugs be inadvertently introduced, increases the chances of them being quickly discovered and fixed.

As already mentioned, the Free Software Foundation does not provide any warranty for PSPP.However, unlike with proprietary software, you are free to engage any third party of your choiceto provide a support contract and/or a warranty service with terms acceptable to you.

Can I use PSPP at school/college/university?

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Many introductory statistics courses specify the use of some statistical analysis software.Some schools specify or recommend the use of PSPP.Others will permit its use if the student asks.If you are enrolled in a course which specifies a proprietary statistical analysis program,we would encourage you to speak to the coordinator of the course and explain that you would prefer to use a free software package (such as PSPP) instead.Today, many schools and universities have a formal policy that students must not be compelledto use proprietary software when an alternative exists.It is worth finding out if this is the case at your institution.Speak to your students' association if necessary.

Are PSPP's results accepted for publication in scientific papers?

What is and is not accepted for publication in a journal is up to that journal's editor. We are not aware of any paper ever having been rejected on the grounds that PSPP was used, but we are aware of studies using PSPP for analysis, which have been published by reputable academic journals.

Please also be aware of PSPP's warranty.

I get an error message: 'Number followed by garbage' and my data is blank.

This warning means that you are trying to import data using DATA LIST and the dataencountered does not match the format you have specified. Check that there are no straycharacters in the data.

If you are running under a non English locale and you are importing decimal data, it islikely that you have data with dots as decimal separators whereas PSPP is expectingcommas. Either change the dots to commas, or place the line SET DECIMAL DOT. atthe top of the file.

Results are displayed only to 2 decimal places. I need more.

At the top of your syntax file, or in your .pspprc file, put (for example) the line SET FORMAT F22.6. which will tell PSPP to print all results to 6 decimal placesand to a formatted width of 22 columns.

I have my data in a spreadsheet. How can I import it into PSPP?

PSPP can directly import spreadsheets created by Gnumeric, LibreOffice and Openoffice.Org. To do so, use theGET DATA command. Alternatively, if using the GUI, click on 'File Import Data'.

We recommend you convert all your spreadsheets either to Gnumeric or Libreoffice format to avoid this extra step.If you have the proprietary spreadsheet program MSExcel you can do this in one of the following ways:

  • First save the data as Comma Separated Values (csv) and import it into the free spreadsheet program
  • Some versions of Excel allow you to save the data directly as an Open Document Spreadsheet (ods) file
  • We encourage everyone to use free software applications. If however for some reason you want to continue using MSOffice you can set default file format to OpenDocumentFormat

Can PSPP open encrypted .savor .sps files?

PSPP includes a tool, named pspp-convert, that can decrypt encrypted .sav or .sps files, given the password. Please read the PSPP manual or the pspp-convert manual, for details.

The SPSS encrypted syntax file format is unacceptably insecure, so to discourage its use PSPP and PSPPIRE do not directly read or write this file format.

How can I get more information on PSPP?

There are several resources for PSPP information. The first is this FAQ andrelated documentation in the distribution and on the web site. The second isthe PSPP source code itself, if you are programmatically inclined.

For discussion with other PSPP users our mailinglist [email protected] is available. You can subscribe to this list at http://lists.gnu.org/mailman/listinfo/pspp-users

Finally, we look forward to all comments and questions related to PSPP.The irc channel is #pspp, which is on the freenode network.

Why don't you merge PSPP with R, GRETL, Octave ... <my favourite program>?

This suggestion comes up from time to time. It is unlikely to happen for anumber of technical, philosophical and legal reasons.

However, we certainly want to provide features which will make PSPPeasier to interact with other programs.If you want an import/export filter or some other feature to help PSPPcomplement your favourite program, then please talk to us about it.

PSPP lacks this feature which I really need. How can I get PSPP tosupport it?

There are several ways:

  • Download the source code and implement it yourself.
  • Hire somebody to implement it for you.
  • Send an email to the developers and ask for the feature. The developers are interested in hearing about what users want.

Any help you can give is appreciated. See the following question.

Can I help out with PSPP development?

Yes. We will gladly accept help in the form of improvements to the code, artwork or documentation.

When you have fixed a bug or improved some parts of PSPP, you cansubmit your patches at http://savannah.gnu.org/patch/?group=pspp

Sometimes users wish to contribute money toward PSPP development. The PSPP developers appreciate the spirit behind this idea, but monetary donations are less useful than other forms of help.

Something doesn't work properly on Windows/Mac.

PSPP is GNU Software and part ofthe GNU System.That means the platforms under which it works best are GNU andGNU/Linux.Like all GNU software, cross platform portability is something which we try to achieve,but it is not the highest priority.Furthermore, supporting free systems takes precedenceover non-free platforms, such as windows or Mac OS,and as a matter of policy PSPP will always work best on a free operating system.

To sum up: Windows and Mac are low on our list of priorities. We recommend youswitch to a free operating system. Bug fixes however,are always accepted.

What does PSPP stand for?

PSPP does not have any official acronymic expansion. But they're easy tocome up with. For example:

  • Perfect Statistics Professionally Presented.
  • Probabilities Sometimes Prevent Problems.
  • People Should Prefer PSPP.

Send along your favorites!

Help! I'm stuck

If you need help using or installing PSPP, you can try one of the following:

  • Reading this FAQ again carefully.
  • The PSPP user's mailing list,
  • Channel #pspp on freenode.
Latest version


A Factor Analysis class

Project description

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This is a Python module to perform exploratory and factor analysis (EFA), with severaloptional rotations. It also includes a class to perform confirmatory factoranalysis (CFA), with certain pre-defined constraints. In expoloratory factor analysis,factor extraction can be performed using a variety of estimation techniques. Thefactor_analyzer package allows users to perfrom EFA using either (1) a minimumresidual (MINRES) solution, (2) a maximum likelihood (ML) solution, or (3) a principalfactor solution. However, CFA can only be performe using an ML solution.

Both the EFA and CFA classes within this package are fully compatible with scikit-learn.Portions of this code are ported from the excellent R library psych, and the sempackage provided inspiration for the CFA class.

Please see the official documentation for additional details.


Exploratory factor analysis (EFA) is a statistical technique used toidentify latent relationships among sets of observed variables in adataset. In particular, EFA seeks to model a large set of observedvariables as linear combinations of some smaller set of unobserved,latent factors. The matrix of weights, or factor loadings, generatedfrom an EFA model describes the underlying relationships between eachvariable and the latent factors.

Confirmatory factor analysis (CFA), a closely associated technique, isused to test an a priori hypothesis about latent relationships among setsof observed variables. In CFA, the researcher specifies the expected patternof factor loadings (and possibly other constraints), and fits a model accordingto this specification.

Typically, a number of factors (K) in an EFA or CFA model is selectedsuch that it is substantially smaller than the number of variables. Thefactor analysis model can be estimated using a variety of standardestimation methods, including but not limited MINRES or ML.

Factor loadings are similar to standardized regression coefficients, andvariables with higher loadings on a particular factor can be interpretedas explaining a larger proportion of the variation in that factor. In thecase of EFA, factor loading matrices are usually rotated after the factoranalysis model is estimated in order to produce a simpler, more interpretablestructure to identify which variables are loading on a particular factor.

Two common types of rotations are:

  1. The varimax rotation, which rotates the factor loading matrix soas to maximize the sum of the variance of squared loadings, whilepreserving the orthogonality of the loading matrix.
  2. The promax rotation, a method for oblique rotation, which buildsupon the varimax rotation, but ultimately allows factors to becomecorrelated.

This package includes a factor_analyzer module with a stand-aloneFactorAnalyzer class. The class includes fit() and transform()methods that enable users to perform factor analysis and score new datausing the fitted factor model. Users can also perform optional otationson a factor loading matrix using the Rotator class.

The following rotation options are available in both FactorAnalyzerand Rotator:

  1. varimax (orthogonal rotation)
  2. promax (oblique rotation)
  3. oblimin (oblique rotation)
  4. oblimax (orthogonal rotation)
  5. quartimin (oblique rotation)
  6. quartimax (orthogonal rotation)
  7. equamax (orthogonal rotation)

In adddition, the package includes a confirmatory_factor_analyzermodule with a stand-alone ConfirmatoryFactorAnalyzer class. Theclass includes fit() and transform() that enable users to performconfirmatory factor analysis and score new data using the fitted model.Performing CFA requires users to specify in advance a model specificationwith the expected factor loading relationships. This can be done usingthe ModelSpecificationParser class.

Note that the ConfirmatoryFactorAnalyzer class is very experimental at this point,so use it with caution, especially if your data are highly non-normal.


Exploratory factor analysis example.

Confirmatory factor analysis example.


  • Python 3.4 or higher
  • numpy
  • pandas
  • scipy
  • scikit-learn


Contributions to factor_analyzer are very welcome. Please file an issueon GitHub, or contact jbiggs@ets.org if you would like to contribute.


You can install this package via pip with:

$ pip install factor_analyzer

Alternatively, you can install via conda with:

$ conda install -c ets factor_analyzer

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