MS Applied Statistics and Data Analytics

The Department of Statistical Science offers the following graduate degree programs: the Ph.D. in statistical science, the Ph.D. in biostatistics and the M.S. in applied statistics and data analytics.

A Master of Science in Applied Statistics and Data Analytics (MASDA) degree from the Department of Statistical Science at SMU prepares you with the statistical foundation and critical thinking skills to tackle today’s problems and those that don’t even exist today. If you have a background that is strong in mathematics, this degree program can help you take the next step to advance into this new and highly sought-after field.

The courses in the Ph.D. curriculum provide students with a strong theoretical foundation in mathematical statistics, statistical computing, and probability, as well as foundations in areas that may be applied in statistical practice. The Ph.D. in biostatistics is conferred by the Department of Statistical Science at SMU in partnership with the University of Texas Southwestern Medical Center at Dallas. Students attain a strong mathematical and statistical foundation such as that provided in the Ph.D. in statistical science curriculum, but they also take courses and engage in research projects that prepare them for a research career in biostatistics.

The M.S. in applied statistics and data analytics (MASDA) degree program provides students with a theoretically-based understanding and proficiency in statistical methods, as well as training in statistical computing, database management, predictive methods, and other data science techniques.

Note: In both Ph.D. programs, a student advances to candidacy after passing comprehensive and qualifying exams, preparing a written prospectus, and giving an oral presentation in a research area on which the dissertation will be based.

Courses

• STAT 6049 - Graduate Full-Time Status
• STAT 6110 - Independent Study in Statistical Science
• STAT 6301 - Experimental Statistics I
• STAT 6302 - Experimental Statistics II
• STAT 6306 - Introduction to Data Science
• STAT 6307 - Introduction to Statistical Computing
• STAT 6309 - Machine Learning Using Python
• STAT 6310 - Independent Study in Statistical Science
• STAT 6311 - Introduction to Mathematical Statistics I
• STAT 6312 - Introduction to Mathematical Statistics II
• STAT 6315 - Survey Sampling
• STAT 6324 - Computational Statistics
• STAT 6327 - Mathematical Statistics I
• STAT 6328 - Mathematical Statistics II
• STAT 6336 - Statistical Analysis I
• STAT 6337 - Statistical Analysis II
• STAT 6341 - Sports Analytics
• STAT 6345 - Linear Regression
• STAT 6346 - Advanced Regression Analysis
• STAT 6350 - Analysis of Lifetime Data
• STAT 6355 - Applied Multivariate Analysis
• STAT 6357 - Categorical Data Analysis
• STAT 6358 - Statistical Analysis of High Throughput Biological Data
• STAT 6360 - Statistical Methods in Epidemiology
• STAT 6363 - Time Series Analysis
• STAT 6366 - Statistical Consulting
• STAT 6367 - Statistical Practice
• STAT 6370 - Stochastic Models
• STAT 6371 - Probability Theory
• STAT 6376 - Stochastic Processes
• STAT 6377 - Multivariate Categorical Data
• STAT 6380 - Mathematical Theory of Sampling
• STAT 6385 - Survey of Nonparametric Statistics
• STAT 6390 - Bayesian Statistics
• STAT 6391 - Bayesian Hierarchical Modeling
• STAT 6395 - Selected Topics in Statistics
• STAT 6397 - Statistical Methods in Clinical Trials
• STAT 6398 - Thesis
• STAT 7011 - Supervised Internship
• STAT 7012 - Supervised Internship
• STAT 7013 - Supervised Internship
• STAT 7100 - Seminar
• STAT 7110 - Supervised Internship
• STAT 7111 - Seminar in Statistical Literature
• STAT 7112 - Seminar in Statistical Literature
• STAT 7300 - Seminar
• STAT 7327 - Advanced Statistical Inference
• STAT 7331 - Modeling Longitudinal and Incomplete Data
• STAT 7362 - Topics in Statistics
• STAT 8049 - Graduate Full-Time Status
• STAT 8105 - Research
• STAT 8198 - Dissertation
• STAT 8398 - Dissertation
• STAT 8698 - Dissertation