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Computing is a significant component of the research, collaborative, and consulting efforts of statisticians and biostatisticians. Below is a (non-exhaustive) list of commonly-used statistical software packages and links to other computing resources in the Department of Bioinformatics and Biostatistics and the University of Louisville.


Statistical Software Packages

  • R – the open-source implementation of the S programming language, and a popular choice among academic and research statisticians. Largely language-based but with menu-driven add-on packages.
  • SAS – frequently used in industry, particularly in insurance and pharmaceutical organizations. Language-based but with menu-driven add-ons.
  • SPSS – popular in the social and health sciences.  Primarily menu-driven but has facilities for language-based coding.
  • Stata –  popular in economics, epidemiology, and the social sciences.  Menu-driven and language-based in equal measure.
  • S-Plus – the proprietary implementation of the S programming language.  Language-driven but with enhanced menus.
  • MATLAB – a language-based package focused on matrix manipulation.  Popular in engineering and the natural sciences.
  • Minitab – a menu-driven system with a spreadsheet-like interface. Popular with Six Sigma adherents and in statistical quality control.

Statistical Computing Resources at UofL

  • Cardinal Research Cluster (CRC) – the research computing cluster, used by many of our faculty and staff as well as researchers all over the university
  • Faculty-developed software – functions and R packages of functions created by our faculty and research staff for recently developed statistical methods

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