The Graduate Interdisciplinary Program in Statistics offers courses of study leading to the Master of Science (M.S.) and Doctor of Philosophy (Ph.D.) degrees in Statistics. A Ph.D. minor and a 12-unit Graduate Certificate in Statistics are also available. The Program 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

• biometry
• bioinformatics
• biostatistics
• econometrics & financial statistics
• educational statistics
• environmental statistics
• mathematical statistics
• operations research & applied probability
• psychometrics
• quantitative risk assessment
• spatial/spatio-temporal analysis
• statistical genetics/genomics
• stochastic modeling

Students entering the Program are expected to have a substantive background in mathematics, including advanced calculus and linear algebra, experience with computer technologies, and at least one introductory course in statistical methods. A previous degree in Statistics or Biostatistics is not necessary, although a degree in either in a mathematical field or a field that makes significant use of quantitative methods is required.

The Graduate Certificate in Statistics consists of 12 units of course work, designed to expand opportunities for potential or current University of Arizona graduate students wishing to obtain a deeper understanding of statistical methodology, inference, and practice, and offers greater depth of focus to their data-analytic training.  The Certificate’s program of study provides a prescribed format for such learning, while also allowing for a flexible curriculum that addresses this need over a wide variety of disciplines.  Students completing the Graduate Certificate and meeting appropriate requirements may also continue on to an M.S. or Ph.D.

The M.S. in Statistics consists of 30 units of course work, 18 of which are made up of core material in the theory of probability and statistics, statistical regression analysis, design of experiments, data management, and training in statistical consulting. An additional 9 units are taken from a list of interdisciplinary courses with emphasis possible in the theory, application, and/or practice of statistics, followed by 3 units for the M.S. Thesis. A non-thesis option is available. The M.S. degree provides the student with a strong underpinning in statistics and is well-suited for those who wish to consider a career in industry or government service. Students completing the M.S. degree and meeting appropriate requirements may also continue on to a Ph.D.

The Ph.D. degree requires a minimum of 74 units, 35 of which are core courses in the advanced theory of probability and statistics, statistical data analysis, design of experiments, the theory of linear models, statistical computing, and as with the M.S., training in statistical consulting. Students entering with an M.S. in Statistics or an M.S. from a comparable field may petition for waiver of and/or credit for selected core courses, subject to any restrictions laid forth by the Graduate College on such waivers or credits. An additional 12 units are taken from a list of interdisciplinary courses with emphasis possible in the theory, application, and/or practice of statistics, to be coordinated with at least 9 further units in an associated minor field of study. The additional interdisciplinary units, coupled with the external minor, allow students to tailor their doctoral program to suit specific statistical/quantitative interests in a targeted subject-matter area. A minimum of 18 units for the Ph.D. dissertation completes the degree program. The dissertation is expected to make a substantive, original contribution to the theory or practice of modern statistics.

The listed Faculty of the Program are actively involved in the supervision and/or instruction of Statistics graduate students. The departmental affiliations of the faculty on this list give an indication of the breadth of their interdisciplinary research expertise. In addition, the Program has a substantial number of Affiliate Faculty who are involved in research with a strong statistical component and who can be called upon to be potential research advisors. The combined network of Regular Statistics Faculty and Affiliate Faculty creates a unique foundation of interdisciplinary research opportunities in statistics.