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Statistical Software: Overview

Resources for learning statistical software.

Geospatial Data Librarian & Statistics Specialist

Jennie Murack

Get help with statistical software

Do you have specific questions about statistics, research methods, or software?

Make an appointment with a consultant at Harvard

Consultations are free to MIT.

Attend a Summer Statistics Program

Statistical software workshops

‚ÄčR Regression Models: Friday, 1/23: 1pm-4pm: Register

R Graphics: Thursday, 1/22: 9:30am-12:30pm: Register

Intro to Stata: Monday, 1/26, 1pm-4pm: Register

Data Management in Stata: Tuesday, 1/27, 1pm-4pm: Register

Regression and Graphing in Stata: Friday, 1/30, 1pm-5pm: Register

Intro to R: Friday, 2/13, 9am-12pm (at Harvard): Register

R Regression Models: Friday, 2/20, 9am-12:30pm (at Harvard): Register

MIT affiliates can attend statistical software workshops at Harvard throughout the year.

See materials from past workshops here.

Overview of Statistical Software Workshop (January 2015)

Description: Do you need to analyze data, but are not sure which program to use? Have you been using one statistical software package for a while and are curious about others? We will learn the strengths and weaknesses of some statistical software programs, see a brief demo of each, and learn how to access them at MIT.

Materials from other workshops can be found here.

Software at MIT

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

Software Strengths Weaknesses Interface Access
R
  • free and open source
  • variety of add-on packages available
  • flexible and robust programming language 
  • steep leaning curve (no GUI)
  • quality of packages varies
  • no standard help resources
command line Athena or download free
SAS
  • powerful data management
  • can handle large, complex datasets
  • high quality graphics
  • work in multiple files at once
  • excels at ANOVA, mixed models, multivariate analysis
  • excellent help resources
  • steep learning curve
  • limited support for survey data
  • difficult to find errors in commands
command line Athena
Stata
  • easy to use
  • can handle complex analysis and data management
  • high quality graphics
  • excels at regression, robust methods, survey data analysis
  • fewer options for personalized programming
GUI and command line Athena or purchase through IS&T
SPSS
  • very easy to use
  • high quality graphics
  • excels at ANOVA, multivariate analysis
  • complex or large datasets
  • 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 and visualization
  • can be used to explore research designs
  • complex or large datasets
  • limited data management tools
  • limited programming options
GUI free for teaching and research through IS&T
Sources:

http://www.ats.ucla.edu/stat/mult_pkg/compare_packages.htm
http://blogs.sas.com/content/jmp/2013/05/21/time-to-move-from-spss-to-jmp/

Transfer data between programs