This list of statistical software has been compiled to help researchers identify statistical tools that may help in their projects. It is a live document and we would be grateful of updates, both advising of new software availability or change in licences and of the removal of any from Warwick systems.
It should be recognised that many of the systems share functionality and the use of any alternative system is a matter of preference. Thus we do not offer any opinions on the quality or relative value of different systems.
The full list of software licences at the University can be found at:
Notes on the table of available software
The list of software below was compiled during April 2013. It will be updated in the light of ad hoc comments as they are received.We have grouped the software packages according to whether general statistical functionality is provided or whether the focus is on more specific uses. We recognise that this is a subjective classification and others, particularly the software developers, might classify the packages differently.Statistical software packages often find favour in particular disciplines because they have been or were originally written for work in a particular discipline. SPSS is an obvious case in point. The initials derive from Statistical Package for the Social Sciences, but for many years have been known simply as SPSS. However, since it is a general purpose package, it may be used elsewhere – one of us has used its clustering algorithms in analysing software for atmospheric dispersion! Nonetheless it is still used mainly in the social sciences. Because of this, we indicate the history and origins of packages as we know them to indicate fit with disciplines.
There is a useful list of software on Wikipedia, see: http://en.wikipedia.org/wiki/Statistical_software.
General Purpose Statistical Packages
Broadly, these packages offer the user and easy way of applying standard estimation, confidence interval and hypothesis testing techniques to general data, usually input in the form of a spreadsheet.
Statistical Packages Designed for a Specific Set of Functions
General Purpose Packages which have some Statistical Functionality
|Software||Functionality||Background||Licence availability, restrictions and links to distributor|
Statistical analysis software
The package covers most statistical procedures to some extent, most strongly on ANOVA and experimental design. There are also a number of elements designed to support quality management. Because perhaps of its pedigree as a tool for teaching statistics, its help functionality is particularly strong, offering help in recognising the appropriateness of particular statistical methods to your data.
|Minitab was developed at Penn State University and has been one of
the standard packages for teaching statistics for over three decades. It has also developed into a reasonably full
general purpose statistical package that may be used in research.
|Site licence purchased by IT Services. Further information and download details: http://www2.warwick.ac.uk/services/its/servicessupport/software/
Minitab is marketed by Minitab Inc (http://www.minitab.com/). Their website contains a range of teaching resources, some chargeable, including a list of text-books which reference Minitab, many providing examples in Minitab code.
Data analysis and graphing software application
|The package provides some basic statistical
functionality, but is primarily a graphical package offering a range of high
quality plots and graphs of publication quality. It is strong on curve fitting.
|Origin’s background lies in the development of
statistical graphics. Its purpose was
originally to provide high quality statistical graphics for publication. Statistical functionality, mainly relating to
curve fitting, has developed since.
|Available to university members only. Further information and download details: http://www2.warwick.ac.uk/services/its/servicessupport/software/
Origin is marketed by OriginLab (http://www.originlab.com/). The site has some support including a set of video tutorials.
|R||R is at its heart a statistical programming and
data manipulation language, capable of being used to perform just about any
statistical analysis. It is also very
strong on graphics. R is used
extensively across academic statistics for developing new statistical
methodology. Being an open project,
there are an enormous number of add-ins and packages available to perform
specific analyses. Some are very well
tested and validated, but others are there purely for others to test and
experiment with. So it is wise to check
the pedigree of any add-in that you use for analysis. Some of the add-ins provide graphical
interfaces making particular analyses or suites of analyses accessible to
inexperienced users (e.g. R Commander and Rattle), but the R package itself is
designed for professional statisticians and researchers.
|‘S’ was developed as a statistical programming language by J.M. Chambers at Bell AT&T Labs. As a language it allows any statistical analysis to be written and run on virtually any data. ‘R’ is a free implementation of a dialect of S. (S-Plus is a commercial implementation: see entry on S-Plus).
As a matter of local history, in 2007 Prof David Firth and Dr Heather Turner of Warwick Statistics won the John M Chambers Statistical Software Award for their Generalized Nonlinear Models (gnm) R package.
|Note that this is public domain software and, while there is reason to be confident in R itself, many add-ins are not tested and validated to commercial standards.
The R website with links for downloads, manuals, FAQs, book lists, etc. is at:
A library of contributed add-in packages is maintained (under the menu item packages) at: