SOFA Statistics icon
SOFA Statistics icon

SOFA Statistics

 20 likes

SOFA Statistics is an open-source statistical package, with an emphasis on ease of use, learn as you go, and beautiful output. The name stands for Statistics Open For All. It has a graphical user interface and can connect directly to MySQL, SQLite, MS Access, and MS SQL Server.

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License model

  • FreeOpen Source

Application type

Country of Origin

  • GB flagUnited Kingdom

Platforms

  • Mac  Should work but no package currently available
  • Windows
  • Linux  Only packaged for Ubuntu
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Features

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  1.  Graphical User Interface
  2.  Database Management Tool
  3.  Reporting

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SOFA Statistics information

  • Developed by

    GB flagDr Grant Paton-Simpson, Paton-Simpson & Associates Ltd
  • Licensing

    Open Source and Free product.
  • Alternatives

    36 alternatives listed
  • Supported Languages

    • English

AlternativeTo Category

Office & Productivity

Our users have written 0 comments and reviews about SOFA Statistics, and it has gotten 20 likes

SOFA Statistics was added to AlternativeTo by pyGrant on Jan 27, 2010 and this page was last updated Oct 22, 2021. SOFA Statistics is sometimes referred to as SOFA.
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What is SOFA Statistics?

SOFA Statistics is an open-source statistical package, with an emphasis on ease of use, learn as you go, and beautiful output. The name stands for Statistics Open For All. It has a graphical user interface and can connect directly to MySQL, SQLite, MS Access, and MS SQL Server. Data can also be imported from CSV or MS Excel files. The main statistical tests available are Independent and Paired t-tests, Wilcoxon signed ranks, Mann–Whitney U, Pearsons chi square, Kruskal Wallis H, one-way ANOVA, Spearmans R, and Pearsons R. Nested tables can be produced with row and column percentages, totals, sd, mean, median, and sum.

SOFA Statistics is written in Python, and the widget toolkit used is wxPython. The statistical analyses are based on functions available through the Scipy stats module.

Analysis and reporting can be automated using Python scripts – either exported directly from SOFA Statistics or manually written.