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Statistical Software: Overview

Resources for learning statistical software.

Contact us

Attend a Summer Statistics Program

Get help with statistical software

Do you need help getting started with statistical software, basic analysis, or visualization?

Contact our Libraries' team at stat-help@mit.edu.

We can provide beginner help with data cleaning, preparation, descriptive statistics, and visualization in a variety of statistical software. However, we do not make decisions about how you should analyze your data. 

Need more advanced help with study design, methodology, or programming? 

Make an appointment with a data scientist at Harvard IQSS.

3 hours of help are provided per project and consultations are free for MIT affiliates. Help is not provided for coursework. Harvard data scientists will also collaborate on select research projects for a fee.

IQSS also offers tutorials for learning R, Python and Stata.

Statistical Software at MIT

All statistical software below can perform common statistical tests and save commands to and run commands from a syntax file.

Software Strengths Weaknesses Interface MIT Access
R
  • free and open-source
  • variety of add-on packages available for all types of analysis
  • steep learning curve
  • quality of packages varies
  • no standard help resources
 command line Athena or free download
SAS
  • powerful data management
  • works well with multiple, large, complex datasets
  • high quality graphics
  • excels at ANOVA, mixed models, & multivariate analysis
  • excellent help resources
  • steep learning curve
  • difficult to find errors in commands
 command line Athena (This is the UNIX version, which can be difficult to use)
Stata
  • easy to use
  • can handle complex analysis and data management
  • high quality graphics
  • excels as regression, robust methods, survey data, public health data
  • fewer options for personalized programming
 GUI, command line Athena, GIS lab computers, purchase through IS&T
SPSS
  • very easy to use
  • high quality graphics
  • excels at ANOVA, multivariate analysis, survey data
  • complex or large datasets
  • more limited data management tools
  • fewer options for personalized programming
 GUI free for faculty and staff through IS&T
JMP
  • very easy to use
  • excels at data exploration, research design, and visualization
  • complex or large datasets
  • limited data management tools
  • fewer options for personalized programming
 GUI free for teaching and research through IS&T