Free statistical software

Introduction
There is a wide variety of free statistical software from a variety of sources, including governments, NGSs, universities, and developed by individuals. Most of it is fairly easy to learn, using menu systems, while a few are command driven. Many of these free software packages have been used in academic research in peer reviewed journals or in publications from major organizations. Some are very popular while others are much less frequently used. In general, though, free statistical software should be seen as a reasonable alternative to the commercial packages.

Sources of free statistical software
Some of the free software is from governmental or NGO organizations, such as Epi Info, from CDC, and IDAMS from UNESCO. Some other software is from smaller or independent organizations or universities, such as Instat or Irristat. The great majority of free statistical software, however, is from individuals. Some commonly used software from individuals include Easyreg, MicrOsiris , OpenStat , and Zelig.

Finally, a couple of other packages are being developed by groups, rather than individuals, but not by established institutions, like universities, governments, or NGOs. Rather these are groups of individuals. PSPP, from the GNU project, is developing into a clone of SPSS, but is free. The R project is also frequently used.

Reviews of free statistical software
There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca and another article that included mainly a brief review of R. Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures. They review several programs and identified which ones, at that time, had the most functionality. At that time, several of the programs may not have had all of the desired ability for advanced statistics. Grant reviewed some of the programing features of R, and briefly mentioned the availability of other programs. A couple of websites that list software also have very brief reviews of each package. The two sites that have these are by StatCon and by Pezzullo. These sites mainly offer a brief list of the features available in the packages.

There is also a journal specifically for statistical software, although the main focus is on commercial software, R and some coding snippets.

These free software packages have been used in a number of scholarly publications, so that at least various journals, NGOs or other organizations regard the packages as valid. For example, OpenStat was used in a research letter to JAMA and in this genome study. Irristat is used in this agricultural report and WinIdams was used in this paper.

Using free statistical software
Most of these packages are menu driven, and can be learned a couple of hours at most, except R, which is generally code driven and requires a much longer time to learn.

In order to use any statistical software appropriately, it is generally a good idea to have a good background in Statistics.