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Statistical Analysis Software

This guides serves as an introduction to some Statistical Analysis Software. It aims to help patrons familiarize with five of the most popular statistical software.

Minitab

     

  • Commonly used in: social science, marketing, education, sociology, manufacturing, agriculture, pharmaceutical science, engineering
  • Menu-driven statistical software, but does have scripting language available for typing commands or creating macros
  • Help documentation located in software as well as online
  • Clear output and graphics with some interactive features
  • Has an “Assistant” feature that includes flowcharts and takes users step-by-step to analyze data properly
  • Great for: data manipulation, editing, and coding; data summary; exploratory analysis; survival analysis; linear and nonlinear modeling; graphical analysis; forecasting; quality assessment and improvement

Available via:

R & RStudio

      R-Programming logo

  • R is a language and environment for statistical computing and graphics.
  • It compiles and runs on a variety of platforms. Here, we recommend RStudio.
  • Commonly used in: statistical science, computational biology, quantitative finance, engineering etc.
  • Scripting programming language
  • Case-sensitive language
  • Multiple add-ons and extensions available
  • Extensive online help manuals and forums
  • Multiple datasets can be handled at once
  • Flexible and customizable analysis and graphics.
  • Great for: data manipulation, editing, and coding; data mining; simulations; survival analysis; linear and nonlinear modeling; data warehousing; multivariate analysis; nonparametric methods; hypothesis testing; categorical analysis; time series analysis; sample size calculations and power analysis; optimization

RStudio logo

  • RStudio is a free and open-source development environment for R. It integrates with LaTeX
  • In the following, we will introduce the language R through RStudio.

Available via:

SAS

    

  • Commonly used in: statistical science, sociology, manufacturing, pharmaceutical science, agriculture, computer science, qualitative finance, engineering, etc.
  • Offers various certifications, which many employers value highly
  • Not case sensitive
  • Multiple add-ons and extensions available
  • Extensive online help manuals and forums
  • Multiple data sets can be handled at once and are stored in various workspaces called (“libraries”)
  • Flexible and customizable analysis and graphics
  • Great for: data manipulation, editing, and coding; data mining; data summary; exploratory analysis; simulations; survival analysis; linear and nonlinear modeling; graphical analysis; forecasting; quality assessment and improvement

Available via:

 

SPSS

    

  • Commonly used in: Social science, Marketing, Education, Sociology, Healthcare, Government
  • Used in conjunction with many common survey platforms, and is the leading software for analyzing survey data
  • Menu-driven statistical software, but does have scripting language available for typing commands or creating macros
  • Plug-ins available for other programming languages, such as JAVA, Python, R, and VB
  • Help documentation located in software as well as online
  • Output and graphics are clear and well organized
  • Great for: data manipulation, editing, and coding; data summary; exploratory analysis; linear and nonlinear modeling; graphical analysis

Available via:

STATA

    

  • Commonly used in: Economics, Sociology, Political science, Pharmaceutical, Epidemiology
  • Utilizes both menu-driven selections and scripting commands
  • Not case-sensitive language
  • Multiple versions available depending on needs (commercial, educational, etc.)
  • Extensive help documentation and technical support
  • Somewhat flexible and customizable
  • Great for: data manipulation, editing, and coding; data mining; data summary; data warehousing; exploratory analysis; simulations; survival analysis; linear and nonlinear modeling; multivariate analysis

Available via: