Free statistical software

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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[1], from CDC, and IDAMS[2] from UNESCO. Some other software is from smaller or independent organizations or universities, such as Instat[3] or Irristat[4]. The great majority of free statistical software, however, is from individuals. Some commonly used software from individuals include Easyreg[5], MicrOsiris[6], OpenStat[7], and Zelig[8].

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[9], from the GNU project, is developing into a clone of SPSS, but is free. The R project[10] 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 There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca[11] and another article by Grant that included mainly a brief review of R[12]. 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[13] and by Pezzullo[14]. These sites mainly offer a brief list of the features available in the packages.

There is also a journal specifically for statistical software[15], 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[16] and in this genome study[17]. Irristat is used in this agricultural report[18] and WinIdams was used in these papers[19], [20].

Using free statistical software

Before using any statistical packages, it is generally a good idea to have a solid background in Statistics. Then the packages can be used to the best advantage, for example, to choose the most appropriate test, to make sure all the necessary assumptions are met, so that the appropriate conclusions can be drawn.

Once the statistical issues are understood, the next step is to decide which package to use. 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, and to some extent CDC's Epi Info, which also takes some time to learn.

Several of the packages also have tutorials. For example, CDC has these tutorials about Epi Info[21], [22]. The CDC page also lists a tutorial from the University of Nebraska [23].

References

  1. ↑ Epi Info, CDC, 2008 http://www.cdc.gov/epiinfo/index.htm.
  2. ↑ IDAMS Statistical Software, http://portal.unesco.org/ci/en/ev.php-URL_ID=2070&URL_DO=DO_TOPIC&URL_SECTION=201.html
  3. ↑ Instat - an interactive statistical package, Statistical Services Centre - University of Reading, 2009. http://www.ssc.rdg.ac.uk/software/instat/instat.html
  4. ↑ Irristat, International Rice Research Instititue, Biometrics and Bioinformatics Unit, http://www.irri.org/science/software/irristat.asp
  5. ↑ Easy Reg International, Herman Bierens, Penn State University, 2008 http://econ.la.psu.edu/~hbierens/EASYREG.HTM
  6. ↑ MicOsiris, Neal Van Eck, Van Eck Computer Consulting http://www.microsiris.com/
  7. ↑ OpenStat, Bill Miller, 2009 http://www.statpages.org/miller/openstat/
  8. ↑ Zelig, Kosuke Imai, Gary King and Olivia Lau , 2009 http://gking.harvard.edu/zelig/
  9. ↑ PSPP, 2008 http://www.gnu.org/software/pspp/
  10. ↑ The R Project, http://cran.r-project.org/
  11. ↑ "A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" Journal of Industrial Technology (Volume 21-2, April 2005), Ms. Xiaoping Zhu and Dr. Ognjen Kuljaca. http://www.nait.org/jit/current.html
  12. ↑ Felix Grant, "Free Statistics Software, Yours, Free to keep....", Scientific Computing World, Sept/Oct 2004, http://www.scientific-computing.com/scwsepoct04free_statistics.html
  13. ↑ List of free statistical software, Open Source & Public Domain Packages with Source Code. StatCon 2006. http://statistiksoftware.com/free_software.html
  14. ↑ Pezzullo, Free Statistical Software, 2009. http://statpages.org/javasta2.html
  15. ↑ Journal of Statistical Software, http://www.jstatsoft.org/
  16. ↑ Future Salary and US Residency Fill Rate Revisited, Mark Ebell. Research letter in JAMA, September 10, 2008—Vol 300, No. 10, p1131-1132. http://jama.ama-assn.org/cgi/reprint/300/10/1131
  17. ↑ Differential gene expression patterns in cyclooxygenase-1 and cyclooxygenase-2 deficient mouse brain. Christopher D Toscano, Vinaykumar V Prabhu, Robert Langenbach, Kevin G Becker, and Francesca Bosetti. Genome Biol. 2007; 8(1): R14. http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1839133
  18. ↑ FAO Plant Production and Protection Paper No. 174, Rome, 2003, Genotype x environment interactions. Challenges and opportunities for plant breeding and cultivar recommendations, http://www.fao.org/DOCREP/005/Y4391E/y4391e00.htm
  19. ↑ N. S. Sapre, N. Pancholi, and S. Gupta, Computational Modeling of Substitution Effect on HIV–1 Non–Nucleoside Reverse Transcriptase Inhibitors with Kier–Hall Electrotopological State (E– state) Indices, Internet Electron. J. Mol. Des. 2008, 7, 55–67, http://www.biochempress.com/cv07_i03.html
  20. ↑ Chawla, Anju. Exploring project selection behavior of academic scientists in India. Research Evaluation, Volume 16, Number 1, March 2007 , pp. 35-45(11). http://www.ingentaconnect.com/content/beech/rev/2007/00000016/00000001/art00004
  21. ↑ Epi Info™ Community Health Assessment Tutorial. The Epi Info™ Community Health Assessment Tutorial was produced by the collaborative efforts of the Centers for Disease Control and Prevention (CDC), the Assessment Initiative (AI), and the New York State Department of Health (NYSDOH). http://www.cdc.gov/epiinfo/communityhealth.htm
  22. ↑ Cholera Outbreak in Rwenshama: Using Epi Info for Windows in an Outbreak Investigation. Coordinating Office for Global Health - DGPHCD, http://www.cdc.gov/cogh/dgphcd/training/softwaretraining.htm
  23. ↑ Introduction to EPI2000. GPVEC Great Plains Veterinary Educational Center. University of Nebraska - Lincoln. http://gpvec.unl.edu/videos/epi-stats.asp
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