(effective Fall 2015)
The Professional Master in Statistics (M.Stat.) Program offers a customized and individualized programs based on the interests and career objectives of the student. Students are allowed to choose either a broad-based or specialized program of study. All choices, however, provide a balanced training in statistical methods, computational statistics, and statistical theory, and are intended to prepare the student to adapt statistical methodologies to practical problems in a professional setting.
Course of Study
The M.Stat. is a non-thesis Master's degree, and does not require an internship. Students are required to take 30 hours of approved coursework, with additional recommended career-enhancing enrichment courses. Depending on the student's selected specialization, the mix of required, track-specific and elective courses will be jointly determined by the student and the graduate advisor. You will meet with your advisor during the first year of the program to select an individualized plan of study, with periodic tune-ups as the program progresses.
The program normally takes three semesters of full-time course work. Students are restricted to no more than four courses in their first semester, with three being preferable. It is also possible to complete the program on a part-time basis.
Core Curriculum — Required Courses
These courses are normally completed by the end of the first 2 semesters
Probability (STAT 518)
Statistical Inference (STAT 519)
Statistical Computing and Graphics (STAT 605)
Introduction to Regression and Statistical Computing (STAT 615)
Advanced Statistical Methods (STAT 616)
These courses are recommended for the specialization track that is to be developed between the MStat student and the advisor (Director of MStat Program). Courses include recommended core and elective courses. The current recommended core courses are listed below; recommended electives and courses for certain tracks such as Applied Statistics for Industry and Preparation for Ph.D. Studies are developed separately. For a description of each specialization, click on the specialization title.
Computational Finance I - Market Models (STAT 686)
Applied Time Series and Forecasting (STAT 621)
Quantitative Financial Analytics (STAT 682)
Generalized Linear Models & Categorical Analysis (STAT 545)
Biostatistics (STAT 553)
Probability in Bioinformatics and Genetics (STAT 623)
Probability and Statistics for Systems Biology (STAT 673)
Bayesian Data Analysis (STAT 622)
Multivariate Analysis (STAT 541)
Simulation (STAT 542)
Data Mining and Statistical Learning (STAT 640)
Quantitative Environmental Decision Making (STAT 685)
Environmental Risk Assessment & Human Health (STAT 684)
Applied Statistics for Industry and Preparation for Ph.D. Studies in Statistics, Mathematical Economics, and Finance
Masters in Computational Science and Engineering (MCSE)
Electives are targeted in the subfield of interest. Students may be asked to take specific courses outside the department, depending on the incoming background of the student, career objectives and funding sources. The links above to curriculum planning for each specialization include suggested electives for each specialization.
Admission to the M.Stat program does not carry any commitment of financial aid, and the student is expected to be fully responsible for tuition and fees throughout the program. Tuition is based on hours taken; full-time tuition is based on registering for at least 9 hours; for more details, see application process.
International students must pay careful attention to rules regarding full-time status and optional and practical training (if needed). The International Students and Scholars Office (OISS) is the source of information on these issues.