Guide to statistics software
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price overview
free of charge
- R software package [1]
commercial
All price are rounded estimates as of Spring 2007 for a single, educational license of the latest version (not upgrades). Prices vary with reseller. Follow the links for exact information. Items are ordered starting with the cheapest price in Euros.
- SigmaStat v3.5 €445 [2] / v3.5 $480 [3]
- SigmaPlot (usually bundled) [4] / v10 $480 [5]
- MatLab GBP370/€500 [6] (requires login)
- SysStat v? €700 [7] / v12 $490 [8]
- JMP v6 €920 [9]
- SPSS v15 Base €1720 [10]
commercial but pricing not yet entered:
- SAS
- Origin
software by license type
open source
- R
commercial
- SPSS
- SysStat, SigmaStat, SigmaPlot
- SAS
- Origin
review extracts
several
"five user friendly, menu-driven programs that are intended mainly for users with beginner to intermediate levels of statistical expertise: JMP, NCSS, Sigmastat, Statistica and True EPISTAT. Of these, the first four are general purpose data analysis packages while True EPISTAT is intended for medical scientists. All have large user manual full of simple examples. None offer anything like the same scope for power analysis as they do for statistical hypothesis testing. This means that a researcher relying solely on one of these packages could analyze a study without being able to properly plan it or check its power. Sigmastat offers the widest scope for planning power or sample size (Table 3), although the ANOVA option doesn’t go beyond one-way. JMP is the most comprehensive in this respect, offering power calculations, tables, and power vs. sample size graphs for almost any fixed effect ANOVA design (but for nothing else). True EPISTAT can calculate approximate power and sample size for a limited assortment of tests and can produce graphs and some very limited tables. In Statistica, power and sample size can be calculated for some one-sample tests using the Process Analysis module, and OC (power vs. sample size) curves can be produced." [11]
SigmaStat
"This is a good starter package. Not very powerful, and not all that flexible, but simple and instructive" [12]
MatLab
"Particular advantages were listed as: ease of customisation, informative error messages, the ability to handle large matrices. The main disadvantage was the time taken to learn the application. The UNIX version is command-line driven."
links
- R Project page, R Statistics on OWW
- Review of visualisation tools in statistics by the Queen's Uni Belfast (Social Sciences)
