Master of Science in Statistics and Data Science

The Statistics & Data Science Interdisciplinary Program offers interdisciplinary courses of study leading to the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Statistics (regular track or statistical informatics track), along with a 12-unit Graduate Certificate. A Ph.D. minor in Statistics is also available for students already registered into a Ph.D. program other than Statistics here at the UA. Our mission is to develop the next generation of data scientists, trained to meet the challenges of modern interdisciplinary data extraction, analysis, and interpretation.The GIDP supports and encourages the central role of statistical and quantitative thinking in the biological, physical, engineering, financial, and social sciences. Necessary training is provided for students to develop core expertise in statistical theory and methodology, and also for students who will apply their statistical knowledge in practical, transdisciplinary research; targeted subject-matter specialties include, but are not limited to biometry, bioinformatics, biostatistics, econometrics & financial statistics, educational statistics, operations research & applied probability, psychometrics, spatialspatio-temporal analysis, statistical geneticsgenomics, stochastic modeling, and quantitative risk assessment.

For admission to the M.S. Program in Statistics, applicants must have or be in the process of completing a Baccalaureate Degree, either in a mathematical field or a field that makes significant use of quantitative methods, with at least a 3.0 overall grade point average (GPA). A previous degree in Statistics or Biostatistics is useful, but not required. All students entering the Program are required to have a substantive background in mathematics, including at least three semesters of Calculus through multivariable/vector calculus (at the level of MATH 125, MATH 129, MATH 223), one semester of Linear Algebra (at the level of MATH 215), and experience with computer technologies. For M.S. and Ph.D. applicants, at least one introductory course in statistical methods (at the level of MATH 263) is required. In addition, at least one semester of upper-division Probability (e.g., MATH 464) and (for Ph.D. students) two semesters of upper-division Real Analysis (e.g., MATH 425A-425B) are strongly recommended. M.S. and Ph.D. applicants must also show scores on the Graduate Record Examination (GRE - general test only) that exceed 75th percentile Quantitative and 50th percentile Verbal. (GRE scores must be dated no older than five years from the time of application to the program.)