• 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

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• 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 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.

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• 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

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• 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

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• 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

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