Carnegie Mellon University

M.S. in Statistics

Many of our Ph.D. students earn a Master of Science (M.S.) in Statistics on the way to achieving their ultimate degree.

The M.S. degree is awarded as a milepost after a certain number of courses and other requirements have been completed. Note that students who have previously earned an M.S. or professional Master’s degree in Statistics are not eligible to earn an additional Master’s from our program. In addition, there are limitations on receiving multiple M.S. degrees from different departments at CMU; you cannot, for instance, receive both an M.S. in Statistics and an M.S. in Machine Learning unless these two degrees are built on disjoint course requirements.

The M.S. has a framework of requirements, as follows:

  • Students must pass the Data Analysis Exam
  • Students must pass Intermediate Statistics (36-705), Applied Regression Analysis (36-707) and Statistical Methods in Machine Learning (36-708)
  • Students must complete a collaborative research experience such as Advanced Data Analysis (36-757 and 36-795) or an independent research project approved by the department
  • Students must also pass additional graduate credits (i.e. 3 courses) chosen from a variety of options. These classes must contain at least nine units from each of the following categories:
    • Statistical computing (36-750) or alternative approved by the department.
    • Statistical methodology (e.g., methods minis, 10-701).
    • Probability or Statistical theory (e.g., 36-709, 36-710, 10-715, 10-716).

There is no thesis requirement for this degree.