Graduate Program

Graduate Program

The Department of Statistical Science has a long and distinguished history of graduate education. Two separate graduate degree programs are offered: (1) Ph.D. and (2) Master of Science in Applied Statistics and Data Analytics (MASDA). The Ph.D. program was established in 1968, and since that time 164 Ph.D. degrees have been awarded. The courses in the Ph.D. curriculum provide students with the strong theoretical foundation in mathematics, statistical inference, and probability needed for students pursuing a research-oriented Ph.D. degree. This degree prepares students for positions in academia, industry, government, or any other employment where state of the art statistical theory or methods are needed.

The explosion of data from sensors and other data collection devices, business processes, surveys, medical instruments, social media, and so forth has created an ever increasing demand for specialists in applied statistics and data analytics. Consequently, beginning in the Fall 2012 semester the Department of Statistical Science at SMU is offering the MASDA degree, which is designed to provide training that is ideally suited to produce graduates who are proficient in statistical methods while at the same time are trained in topics such as data base management, the use of SAS and other statistical software, and data mining that are necessary tools of today’s data analysts.

Written and oral presentation skills are developed throughout both graduate programs, and graduates are prepared to perform as highly trained professional statisticians upon graduation. Computational skills are extensively developed and emphasized in a variety of courses in both programs. This document briefly describes the two programs. Details about the curriculum and degree requirements are contained in the document.

Graduate Curriculum


The emphasis in the Ph.D. program is on developing a fundamental breadth and depth in both theory and applications. During the first year in the program all Ph.D. students are required (unless previous coursework is deemed equivalent by the Graduate Advisor and Chair of the department) to complete a two-semester course in theoretical principles of statistics, Mathematical Statistics (6327, 6328), a two semester course in statistical methods, Statistical Analysis (6336, 6337), an introductory course in statistical computing, Computational Statistics using R (6304), and Regression Analysis (6345). Students continue to take courses during the second and third years in the program.  At the end of the first year students will be assigned an advisor, and with the aid of the advisor, each student will draw up a course schedule which should reflect both the departmental requirements and the student's interests. Consulting (6366), Probability Theory (6371) and Advanced Inference (7327) are courses that are required for the Ph.D. degree and are taken during the second and third years.

Two sets of exams are given to Ph.D. students. The Basic exams are given at the end of the first year, and the Ph.D. Qualifying exam is given at the end of the second year.  After passing the Basic and Qualifying exams, the student should select a faculty member who agrees to direct the student’s dissertation research. After an intended research area is identified, a doctoral candidate may, with approval of the Graduate Advisor and the dissertation director, elect to take one specialized study course each semester of the third year that will focus explicitly on the dissertation research topic. Students are admitted into candidacy after passing both the Basic and Qualifying exams, preparing a written prospectus, giving an oral presentation in a research area on which the dissertation will be based, and receiving approval of the prospectus from his or her dissertation committee. The oral defense of the written dissertation is the culmination of the student's training. The written dissertation demonstrates the student's ability to conduct research at an advanced and sophisticated level.

Students in the Ph.D. program may obtain an M.S. in Statistical Science along the way to the Ph.D. degree or as a terminal degree if they leave the program early for personal or academic reasons.  The requirements for the M.S. in Statistical Science are the successful completion of the required 36 hours of coursework and passing the Basic exams at an appropriate level.


The focus of the MASDA degree is to provide students with training in a variety of statistical methods and areas of application. The program emphasizes the use of databases and statistical packages (such as SAS and R) for performing data analysis.  Students learn to consult with clients, properly analyze data, and report the results both orally and in professional reports. The MASDA degree is ideal for (a) students who have recently received an undergraduate degree (both US and international) who seek to prepare for a career in data analytics, (b) professionals who are employed locally in industry, medical and/or pharmaceutical fields, government, or business and find that their careers require more statistical analysis than their previous degrees had prepared them to do, and (c) undergraduate statistics majors at SMU who extend their training by one year to obtain the MASDA degree.

The MASDA degree is considered to be a terminal masters’ degree in the sense that it prepares students to directly enter the marketplace as applied statisticians/data analysts. In general, the courses are less mathematically demanding than those in our Ph.D. track.  However, a foundation in calculus (through multivariable calculus) is a requirement for entry into the program. Electives can be used to provide focus in a particular area (e.g. biostatistics). No tuition or TA support is available for students in this program.  

The MASDA degree requirements include completion of 36 credit hours of coursework.  Required courses include Experimental Statistics (5371, 5372), Mathematical Statistics (5373, 5374), SAS (5304), Computational Statistics using R (6304), and Statistical Consulting (6366). We expect that students will complete the degree within 18-24 months, depending on the number of courses they take at a time.