This course is designed to support MA students doing research in preparation to apply for a Ph.D. after graduation.*  

To be eligible:  

  • Research project and faculty mentor must be identified before a student can register.
  • The faculty mentor must be an academic researcher (professor or research scientist under a university setting). Columbia faculty is preferred. 

This research experience will be counted towards the MA in Statistics Degree if the project is relevant to the educational goals of our program.  Upon completion, a final report/paper will be required and given a grade by the professor.  

Application Process 

At the start of each semester, an announcement will be sent to all MA Statistics Students with the deadline to apply.

Any student working on an eligible research project may send an email to Professor Alemayehu (da15@columbia.edu). 

The email should include:   

  • A description of the research project
  • Confirmation from the faculty mentor.  

Once the project is approved by Professor Alemayehu, a student may contact Dr. Turkowitz about course entry.  

This course may be taken for one credit (Fall & Spring Semesters) or for zero credit (Summer Semester).   This course may count for graduation once, but may not be repeated for additional graduation credit. 

Questions about the course or about the research component of the course should be sent to Professor Alemayehu (da15@columbia.edu).  

_____________________________

*Students who are looking for research projects are encouraged to participate in the activities organized by the Ma2PhD club.  

Students who are not interested in pursuing a Ph.D. after graduation are recommended to focus instead on class projects, participate in activities organized by on-campus student associations such as the Statistics club or Columbia Data Science Society, and compete in data science hackathons/competitions.  

All students are strongly encouraged to prioritize their performance in core required and elective courses before considering a research project or any extracurricular data science experience.