Master of Statistics (MStat) Degree

Program Learning Outcomes for the MStat Degree 

Upon completing the MStat degree, students will be able to:

  1. Master fundamental theory in probability and statistics.
  2. Become familiar with a broad range of statistical methods for applications.
  3. Become proficient at statistical computing.
  4. Develop effective communication skills as a professional statistician.

Requirements for the MStat Degree 

The MStat degree is a non-thesis master's degree. For general university requirements, please see Non-Thesis Master's Degrees. For additional requirements, regulations, and procedures for all graduate programs, please see All Graduate Students. Students pursuing the MStat degree must complete:

  • A minimum of 30 credit hours to satisfy degree requirements.
  • A minimum of 30 credit hours of graduate-level study (coursework at the 500-level or above).
  • A minimum of 24 credit hours must be taken at Rice University.
  • A minimum residency enrollment of one fall or spring semester of part-time graduate study at Rice University.
  • The requirements of one area of specialization (see below for areas of specialization). The MStat degree program offers four areas of specialization:
    • Bioinformatics, Statistical Genetics, and Biostatistics, or
    • Environmental Statistics, or
    • Financial Statistics and the Statistics of Risk, or
    • Statistical Computing and Data Mining.
  • A minimum overall GPA of 2.67.
  • A minimum GPA of 2.67 in required coursework.

The courses listed below satisfy the requirements for this degree program. In certain instances, courses not on this official list may be substituted upon approval of the program's academic advisor, or where applicable, the department or program's Director of Graduate Studies. (Course substitutions must be formally applied and entered into Degree Works by the department or program's Official Certifier.) Students and their academic advisors should identify and clearly document the courses to be taken.

Summary

Total Credit Hours Required for the MStat Degree30

Degree Requirements

Core Requirements 1
STAT 518PROBABILITY3
STAT 519STATISTICAL INFERENCE3
STAT 605R FOR DATA SCIENCE3
STAT 615REGRESSION AND LINEAR MODELS3
STAT 616ADVANCED STATISTICAL METHODS3
Area of Specialization 2
Select up to 5 from any of the following Areas of Specialization:6-15
Bioinformatics, Statistical Genetics, and Biostatistics
GLM & CATEGORICAL DATA ANALYSIS
SURVIVAL ANALYSIS
BIOSTATISTICS
PROBABILITY IN BIOINFORMATICS AND GENETICS
Environmental Statistics
ENVIRONMENTAL RISK ASSESSMENT & HUMAN HEALTH
ENVIRONMENTAL STATISTICS AND DECISION MAKING
Financial Statistics and the Statistics of Risk
APPLIED TIME SERIES AND FORECASTING
QUANTITATIVE FINANCIAL ANALYTICS
MARKET MODELS
Statistical Computing and Data Mining
BAYESIAN STATISTICS
MULTIVARIATE ANALYSIS
SIMULATION
STATISTICAL MACHINE LEARNING
Elective Requirements
Select up to 9 credit hours of remaining coursework from approved electives in a targeted area of interest to reach 30 total credit hours. 30-9
Total Credit Hours30

Footnotes and Additional Information 

Approved Electives

Depending on the student's interest, up to 15 credit hours of area of specialization and elective requirements may be chosen from the following typically approved coursework, in conjunction with the MStat advisor.

Approved Departmental (STAT) Electives0-15
NEURAL MACHINE LEARNING I
TOPICS IN METHODS AND DATA ANALYSIS
ADVANCED PSYCHOLOGICAL STATISTICS I
ADVANCED PSYCHOLOGICAL STATISTICS II
INTRODUCTION TO BIOSTATISTICS
FOUNDATIONS OF STATISTICAL INFERENCE I
and FOUNDATIONS OF STATISTICAL INFERENCE II
INTERNSHIP IN STATISTICAL MODELING
FUNCTIONAL DATA ANALYSIS
NONPARAMETRIC FUNCTION ESTIMATION
ADVANCED TOPICS IN TIME SERIES
APPLIED STOCHASTIC PROCESSES
MATHEMATICAL PROBABILITY I
MATHEMATICAL PROBABILITY II
INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
NEURAL MACHINE LEARNING AND DATA MINING II
COMPUTATIONAL ECONOMICS
SAS STATISTICAL PROGRAMMING
ECONOMETRICS I
ECONOMETRICS II
TOPICS IN CLINICAL TRIALS
GRAPHICAL MODELS AND NETWORKS
QUANTITATIVE FINANCIAL RISK MANAGEMENT
STOCHASTIC MODELS IN POPULATION DYNAMICS AND POPULATION GENETICS
Approved Electives outside Statistics
FINANCIAL ECONOMICS I
CORPORATE FINANCE
ANALYSIS II
COMPUTATIONAL SCIENCE I
NUMERICAL METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS
NUMERICAL ANALYSIS II
OPTIMIZATION THEORY
NUMERICAL OPTIMIZATION
LINEAR AND INTEGER PROGRAMMING
ADVANCED STOCHASTIC MECHANICS
APPLIED MONTE CARLO ANALYSIS
APPLICATION OF MOLECULAR SIMULATION AND STATISTICAL MECHANICS
SYSTEMS BIOLOGY OF HUMAN DISEASES
GRADUATE OBJECT-ORIENTED PROGRAMMING AND DESIGN
MULTI-CORE COMPUTING
STATISTICAL MACHINE LEARNING
BIOINFORMATICS: SEQUENCE ANALYSIS
PROFESSIONAL DEVELOPMENT FOR BIOMEDICAL INFORMATICS
GRADUATE DESIGN AND ANALYSIS OF ALGORITHMS
DYNAMIC OPTIMIZATION
ADVANCED TOPICS IN ENERGY ECONOMICS
TOPICS IN ECONOMETRICS II
DATA DRIVEN APPROXIMATION OF DYNAMICAL SYSTEMS
STATISTICAL SIGNAL PROCESSING
INFORMATION THEORY
IMAGING AT THE NANOSCALE
SPECIAL TOPICS
FUNDAMENTALS OF MACHINE LEARNING
BUSINESS AND URBAN ANALYTICS
COMPLEX ANALYSIS
FUTURES AND OPTIONS I
FUTURES AND OPTIONS II
MERGERS AND ACQUISITIONS
ENERGY DERIVATIVES
QUANTUM MECHANICS I
STATISTICAL PHYSICS
BIOLOGICAL PHYSICS
FUNDAMENTALS OF QUANTUM OPTICS
ADVANCED TOPICS IN PHYSICS

Policies for the MStat Degree

Department of Statistics Graduate Program Handbook

For more detailed information regarding the MStat degree program policies, please see Statistics department's Graduate Handbook, which can be found here: http://gradhandbooks.rice.edu/2018_19/Statistics_Graduate_Handbook.pdf

Program Restrictions and Exclusions

Students pursuing this degree should be aware of the following program restriction:

  • Courses comprising the 30-credit hour requirement shall not be taken or completed on a pass/fail grading basis.

Transfer Credit 

For Rice University’s policy regarding transfer credit, see Transfer Credit. Some departments and programs have additional restrictions on transfer credit. Students are encouraged to meet with their academic program’s advisor when considering transfer credit possibilities.

Additional Information 

For additional information, please see the Statistics website: https://statistics.rice.edu/why-mstat

Opportunities for the MStat Degree

Additional Information 

For additional information, please see the Statistics website: https://statistics.rice.edu/why-mstat