Master of Science in Statistics

To satisfy the MS degree requirements, the Mathematical Sciences Department currently offers a choice between three tracks:

• Statistics track Students who pursue this track receive a solid foundation and deep background in theoretical and applied statistics. This prepares them for possible continuation in the Ph.D. program in statistics at UT Dallas or another major research university or the opportunity to enter the job market.
• Applied Statistics Track: Students who choose this track typically seek immediate employment after completing their degree and do not plan to continue their education at the doctoral level. This track is also popular among students who already have a background in another discipline but would like to build expertise in statistics to enhance their employment opportunities.
• Data Science track: Students who choose this interdisciplinary track take a balanced mix of courses in statistics, computer science, and mathematics in order to become a data scientist, and take on the challenges of Big Data. Upon graduation, these students seek employment or may continue into a Ph.D. program in data science.

Degree Requirements

The MS degree in Statistics requires completion of 12 approved graduate courses, for a total of 36 semester credit hours. Among these courses, there will be at least 7 courses in Statistics, including 5 specified ones. The other 5 courses are electives, which may be in Statistics, Mathematics, or another discipline, according to the student's professional interests and career goals. All such decisions are made in consultation with the statistics graduate advisor and are subject to the advisor's approval.

Some students choose to do research at the MS level under the supervision of one of the professors and to write a thesis. The thesis must be approved by the Head of the Mathematical Sciences Department. Once the research project is completed, the thesis requires a formal defence in front of the thesis committee. A MS thesis project can be counted as 3 or 6 semester credit hours towards the required 36 hours.

Each student must earn a 3.0 minimum GPA in the courses listed for the student's program.

To satisfy the MS degree requirements, we currently offer a choice between three specializations - Statistics, Applied Statistics, and Data Science.

Statistics Specialization (MS)

1. Five Core Courses:

• STAT 6331 Statistical Inference I
• STAT 6337 Advanced Statistical Methods I
• STAT 6338 Advanced Statistical Methods II
• STAT 6339 Linear Statistical Models
• STAT 6341 Numerical Linear Algebra and Statistical Computing
  • STAT 6331 Statistical Inference I
  • STAT 6337 Advanced Statistical Methods I
  • STAT 6338 Advanced Statistical Methods II
  • STAT 6339 Linear Statistical Models
  • STAT 6341 Numerical Linear Algebra and Statistical Computing

1. Two courses selected from different specialization groups:

• Statistics Specialization Group One
• STAT 6329 Applied Probability and Stochastic Processes
• STAT 6343 Experimental Design
• STAT 7334 Nonparametric and Robust Statistical Methods
  • STAT 6329 Applied Probability and Stochastic Processes
  • STAT 6343 Experimental Design
  • STAT 7334 Nonparametric and Robust Statistical Methods
• Statistics Specialization Group Two
• STAT 6348 Applied Multivariate Analysis
• STAT 7331 Multivariate Analysis
  • STAT 6348 Applied Multivariate Analysis
  • STAT 7331 Multivariate Analysis
• Statistics Specialization Group Three
• STAT 6347 Applied Time Series Analysis
• STAT 7338 Time Series Modeling and Filtering
  • STAT 6347 Applied Time Series Analysis
  • STAT 7338 Time Series Modeling and Filtering

• Statistics Specialization Group One

• STAT 6329 Applied Probability and Stochastic Processes
• STAT 6343 Experimental Design
• STAT 7334 Nonparametric and Robust Statistical Methods
  • Statistics Specialization Group Two
• STAT 6348 Applied Multivariate Analysis
• STAT 7331 Multivariate Analysis
  • Statistics Specialization Group Three
• STAT 6347 Applied Time Series Analysis
• STAT 7338 Time Series Modeling and Filtering

1. Students must choose the remaining courses as electives approved by the graduate advisor for Statistics. Up to two of the following prerequisite 5000-level courses may be counted as electives:

• MATH 5301 Elementary Analysis I
• MATH 5302 Elementary Analysis II
• STAT 5351 Probability and Statistics I
• STAT 5352 Probability and Statistics II
  • MATH 5301 Elementary Analysis I
  • MATH 5302 Elementary Analysis II
  • STAT 5351 Probability and Statistics I
  • STAT 5352 Probability and Statistics II

Applied Statistics Specialization (MS)

1. Five core courses:

• STAT 5351 Probability and Statistics I
• STAT 5352 Probability and Statistics II
• STAT 6337 Advanced Statistical Methods I
• STAT 6338 Advanced Statistical Methods II
• STAT 6341 Numerical Linear Algebra and Statistical Computing
  • STAT 5351 Probability and Statistics I
  • STAT 5352 Probability and Statistics II
  • STAT 6337 Advanced Statistical Methods I
  • STAT 6338 Advanced Statistical Methods II
  • STAT 6341 Numerical Linear Algebra and Statistical Computing

1. Two or more courses are selected from the following list:

• STAT 6329 Applied Probability and Stochastic Processes
• STAT 6343 Experimental Design
• STAT 6347 Applied Time Series Analysis
• STAT 6348 Applied Multivariate Analysis
  • STAT 6329 Applied Probability and Stochastic Processes
  • STAT 6343 Experimental Design
  • STAT 6347 Applied Time Series Analysis
  • STAT 6348 Applied Multivariate Analysis

1. The remaining elective courses can be chosen in Statistics (e.g., STAT 6326 Sampling Theory, STAT 6V99 Statistical Consulting, STAT 6390 Topics in Statistics - Level 6, etc.) or in other disciplines, and must be approved by the advisor. Many students use this option to build expertise in another subject to enhance their employment opportunities.

Data Science Specialization (MS)

• CS 5303 Computer Science I
• CS 5343 Algorithm Analysis and Data Structures2
• CS 6307 Introduction to Big Data Management and Analytics for non-CS-Majors
• CS 6375 Machine Learning
• MATH 6312 Combinatorics and Graph Theory
• STAT 5351 Probability and Statistics I
• STAT 5352 Probability and Statistics II
• STAT 6337 Advanced Statistical Methods I
• STAT 6338 Advanced Statistical Methods II
• STAT 6348 Applied Multivariate Analysis
• STAT 6340 Statistical and Machine Learning
• Plus one guided elective.

Other Requirements

Electives must be approved by the assigned graduate advisor. Courses from other disciplines may also be used upon approval. Substitutions for required courses may be made if approved by the assigned graduate advisor. Instructors may substitute stated prerequisites for students with equivalent experience.

The Statistics MS degree curriculum at the University of Texas at Dallas offers a balanced list of applied and theoretical graduate courses in Statistics and attractive electives. During their study, our MS students acquire the necessary skills that make them highly competitive in the modern job market. Our recent graduates are currently employed as statisticians, biostatisticians, quantitative analysts, managers, actuaries, and so on, or they continue into doctoral degree programs.

Graduates of the program seek positions such as professor in an academic institution, or professional in the industry, government, or finance and a researcher in the public or private sectors. Available emphases ensure that candidates can tailor their future careers by having targeted their educational background to their research interests.

The jobs of a mathematician consistently appear among the top jobs in the rankings of 200 jobs by CareerCast’s Jobs Rated Almanac based upon factors such as work environment, income, hiring outlook, and stress. For more information about careers in mathematics, view the career page of the American Mathematical Society.