MA Statistics: Computing

The following is a list of optional courses on programming skills and statistics review that students can participate in before the first semester starts (or during the program as well). Everything is optional, but it will be very helpful if incoming students are skillful in these areas. We are not necessarily endorsing these courses, but recognizing that these courses cover a significant amount of topics necessary to start your study here in Binghamton.

• Programming (recommended for all students)

  • R Basics (edX - Harvard University) Build a foundation in R and learn how to wrangle, analyze, and visualize data.

  • R Programming for Data Science (Coursera - IBM) Manipulate primitive data types, control flow with conditions and loops, write functions, construct and manipulate R data structures.  
  • Python Programming for Everybody (Coursera - University of Michigan). Learn basics of the Python programming, use variables to store, retrieve and calculate information, utilize core programming tools such as functions and loops
  • SQL for Data Science (Coursera - UC Davis)
• Statistics Review (recommended for students who seek to strengthen their background in statistics)
  • Statistics and R (edx - Harvard University)
  • Statistics with R Specialization (Coursera - Duke University)

Incoming students are expected to have a laptop to complete their coursework. The university provides some software licenses for students; please check with the ITS department for details.

Students are also expected to be technologically curious and familiar with a variety of business and statistical software. Below is a sample list of such software.

• Operating systems / business and file management
  • Windows, Linux / UNIX
  • Microsoft Office
  • Google Docs, Sheets, Forms
  • GitHub
  • Adobe Acrobat
  • FileZilla
  • WinRAR
  • SSH Secure Shell Client
• Programming, database and statistical computing
  • R and RStudio
  • Python and Project Jupyter
  • Google Colab
  • MATLAB
  • Tableau
  • MySQL
  • SAS
• Documentation
  • MiKTeX
  • WinEdt, TeXnicCenter, LyX, Texmaker, or Overleaf