Free statistical software: Difference between revisions

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'''Free statistical software''' comes from a variety of sources, including governments, non-governmental organizations (NGOs) like UNESCO, 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.
'''Free statistical software''' comes from a variety of sources, including governments, non-governmental organizations (NGOs) like UNESCO, 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.

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Free statistical software comes from a variety of sources, including governments, non-governmental organizations (NGOs) like UNESCO, 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 packages are from governmental or NGO organizations, such as Epi Info, from CDC[1], and IDAMS from UNESCO[2]. Some other software packages are from smaller or independent organizations or universities, such as Instat[3] or Irristat[4]. A couple of other packages are being developed by groups of volunteer individuals. PSPP[5], from the GNU project, is developing into a clone of SPSS, but is free. The R project[6] is also very frequently used. A large proportion of free statistical software packages, however, are from individuals. Some commonly used software packages from individuals include Easyreg[7], MicrOsiris[8], OpenStat[9], and Zelig[10].

In some cases, the statistical software packages, along with many other software packages, were developed for the purposes of making key technologies available to those who could not otherwise afford them, to empower development[11]. In other cases, the packages were developed as teaching aids[9],[3]. Other packages were developed for specific purposes but can be more generally used. Examples are Irristat[4], developed for agricultural analysis, and Epi Info[1], developed for public health.

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[12] and another article by Grant that included mainly a brief review of R[13]. 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. One other paper reviews statistical packages, mainly commercial, but includes R[14]. One article reviews EasyReg and includes a discussion of it's accuracy[15]. There has been only one review that compared the output of various packages[16]. In this review, all of the packages read either text files or excel format. All of the packages gave exactly the same results for correlation and regression. For comparison, the packages also gave the same regression results as did excel. One of the main differences among the packages was that, for the example data set used, some packages could only handle data sets with no missing, while others appeared to be able to handle missing values.

A couple of websites that list software also have very brief reviews of each package. The two sites that have these are by StatCon[17] and by Pezzullo[18]. These sites mainly offer a brief list of the features available in the packages. Similarly, one bachelors thesis compares the statistical procedures available on free statistical packages[19]. In this review, R had all of the procedures, OpenStat had 16, MacAnova had 15, and Microsiris had 12. The others had from 8 to 11 of the procedures.

There is also a journal specifically for statistical software[20], 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[21] and in this genome study[22]. Irristat is used in this agricultural report[23] and WinIdams was used in these papers[24], [25].

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[26],[27]. The CDC page also lists a video slide show tutorial from the University of Nebraska [28], and another site has on line training classes[29]. One faculty member from Emory's School of Public Health has a number of introductory manuals[30]. R has a large number of tutorials and manuals, in English and other languages[31],[32],[33], and a faq site[34].

A few of the packages have an email discussion list including R[35], OpenStat[36], and PSPP[37].

References

  1. ↑ 1.0 1.1 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. ↑ 3.0 3.1 Instat - an interactive statistical package, Statistical Services Centre - University of Reading, 2009. http://www.ssc.rdg.ac.uk/software/instat/instat.html
  4. ↑ 4.0 4.1 Irristat, International Rice Research Instititue, Biometrics and Bioinformatics Unit, http://www.irri.org/science/software/irristat.asp
  5. ↑ PSPP, 2008 http://www.gnu.org/software/pspp/
  6. ↑ The R Project, http://cran.r-project.org/
  7. ↑ Easy Reg International, Herman Bierens, Penn State University, 2008 http://econ.la.psu.edu/~hbierens/EASYREG.HTM
  8. ↑ MicOsiris, Neal Van Eck, Van Eck Computer Consulting http://www.microsiris.com/
  9. ↑ 9.0 9.1 OpenStat, Bill Miller, 2009 http://www.statpages.org/miller/openstat/
  10. ↑ Zelig, Kosuke Imai, Gary King and Olivia Lau , 2009 http://gking.harvard.edu/zelig/
  11. ↑ UNESCO. 03-11-2004 . In Focus: Communication and Information Sector's In Focus service. UNESCO and Software. http://portal.unesco.org/ci/en/ev.php-URL_ID=17447&URL_DO=DO_TOPIC&URL_SECTION=201.html
  12. ↑ "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
  13. ↑ Felix Grant, "Free Statistics Software, Yours, Free to keep....", Scientific Computing World, Sept/Oct 2004, http://www.scientific-computing.com/scwsepoct04free_statistics.html
  14. ↑ Edward J. Wegman and Jeffrey L. Solka. 2005. Statistical Software for Today and Tomorrow. http://www.galaxy.gmu.edu/ (listed as "A Guide to Statistical Software".
  15. ↑ Hwan-sik Choia and Nicholas M. Kiefer, Software evaluation: EasyReg International. International Journal of Forecasting. Volume 21, Issue 3, July-September 2005, Pages 609-616. http://dx.doi.org/10.1016/j.ijforecast.2005.02.003
  16. ↑ Shackman, Gene. 2006. "Comparing free statistical software for data sets with no missing values" and "Comparing free statistical software, Handling missing data". Both available here "Free Software" http://gsociology.icaap.org/methods/soft.html
  17. ↑ List of free statistical software, Open Source & Public Domain Packages with Source Code. StatCon 2006. http://statistiksoftware.com/free_software.html
  18. ↑ Pezzullo, Free Statistical Software, 2009. http://statpages.org/javasta2.html
  19. ↑ Paivi Lankinen and Anna Tanhuala. 2008. Internationalization of Software Companies: Case - Le Sphinx, France. School of Business Administration, Jyvaskyla University of Applied Sciences. Appendix 1, Comparing free statistical software. https://oa.doria.fi/handle/10024/38544
  20. ↑ Journal of Statistical Software, http://www.jstatsoft.org/
  21. ↑ 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
  22. ↑ 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
  23. ↑ 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
  24. ↑ 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
  25. ↑ 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
  26. ↑ 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
  27. ↑ 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
  28. ↑ Introduction to EPI2000. GPVEC Great Plains Veterinary Educational Center. University of Nebraska - Lincoln. http://gpvec.unl.edu/videos/epi-stats.asp
  29. ↑ The North Carolina Center for Public Health Preparedness Training Website http://nccphp.sph.unc.edu/training/index.html
  30. ↑ Kevin's Web Page. Kevin M. Sullivan, PhD, MPH, MHA. Department of Epidemiology and Global Health. Rollins School of Public Health of Emory University. http://www.sph.emory.edu/~cdckms/
  31. ↑ Contributed Documentation. http://cran.r-project.org/other-docs.html.
  32. ↑ William Revelle, Using R for psychological research: A simple guide to an elegant package, 2008, http://personality-project.org/r/
  33. ↑ Dong-Yun Kim, MAT 356 R Tutorial, Spring 2004. http://www.math.ilstu.edu/dhkim/Rstuff/Rtutor.html
  34. ↑ R FAQ. Frequently Asked Questions on R. Version 2.8.2009-03-18. ISBN 3-900051-08-9 http://lib.stat.cmu.edu/R/CRAN/doc/FAQ/R-FAQ.html
  35. ↑ R-help -- Main R Mailing List: Primary help. https://stat.ethz.ch/mailman/listinfo/r-help
  36. ↑ OpenStatHelp http://tech.groups.yahoo.com/group/OpenStat/
  37. ↑ Pspp-users -- PSPP user discussion, http://lists.gnu.org/mailman/listinfo/pspp-users
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