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2. Free statistical software - Wikipedia

   en.wikipedia.org/wiki/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 There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics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.

3. StatCrunch - Wikipedia

   en.wikipedia.org/wiki/StatCrunch

   StatCrunch is a web-based statistical software application from Pearson Education. StatCrunch was originally created for use in college statistics courses. As a full-featured statistics package, it is now also used for research and for other statistical analysis purposes.

4. List of statistical software - Wikipedia

   en.wikipedia.org/wiki/List_of_statistical_software

   Rguroo Statistical Software - An online statistical software designed for teaching and analyzing data; S-PLUS – general statistics package; SAS (software) – comprehensive statistical package; SHAZAM (Econometrics and Statistics Software) – comprehensive econometrics and statistics package; SigmaStat – package for group analysis

5. Comparison of statistical packages - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_statistical...

   "A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" (PDF). Journal of Industrial Technology. 21 (2). Archived from the original (PDF) on October 25, 2005.

6. R (programming language) - Wikipedia

   en.wikipedia.org/wiki/R_(programming_language)

   R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.

7. Weka (software) - Wikipedia

   en.wikipedia.org/wiki/Weka_(software)

   Waikato Environment for Knowledge Analysis (Weka) is a collection of machine learning and data analysis free software licensed under the GNU General Public License.It was developed at the University of Waikato, New Zealand and is the companion software to the book "Data Mining: Practical Machine Learning Tools and Techniques".