Statistics and Probability


Please direct inquiries about our graduate program to:

Faculty members: Hui-Hsiung Kuo, Arnab Ganguly, P. Sundar, and Li Chen

This will require Math 3355 and Math 4056 or equivalents as prerequisites. Knowledge of computer packages such as SAS, SPSS will be required to complete the degree program. It is envisioned that this concentration will attract students in Experimental Statistics, Control, Communications, Signal Processing etc. The student will write an M.S. thesis involving Statistics/Random Processes.

The following (or equivalents) are required Mathematics courses:

  1. Math 7360: Probability Theory
  2. Math 7380: Stochastic Processes.

The other Mathematics courses could be Real Analysis I, Control Theory, Graph Theory, Ordinary or Partial Differential Equations, Discrete Optimization, Linear Algebra, etc.

To exemplify the program in more detail the students should further take at least two courses, equivalent to those from the following three groups:

  1. ES 7013: Statistical Inference II
  2. ES 7034: Regression Analysis
  3. ES 7037: Multivariate Analysis
  • EE 7670: Communication Networks
  • EE 7672: Switching and Broadband networks
    1. EE 7520: Optimal Control Theory
    2. EE 7540: Optimization of Stochastic Dynamic Systems