The GIDP in Statistics 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), a 12-unit Graduate Certificate, and a Ph.D. minor for students already registered into a Ph.D. program other than Statistics 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.
Certificate students are often nontraditional students, several years removed from the university education and possessing considerable work experience. We have seen applications from those in the high tech industries (largely Raytheon Missile Systems), technical staff involved in data intensive science looking to improve their knowledge of modern statistics, and former high school math/stat teacher looking for a change in career. With such an extensive and diverse set of backgrounds, the consideration for admission of these applicants requires an examination beyond the transcript to the nature of their work experience. The Certificate program may be completed either online or on campus.
If you have questions on the admissions process, please contact Melanie Bowman, Program Coordinator, at firstname.lastname@example.org.
The Graduate College sponsors several Graduate Interdisciplinary Programs (GIDPs) in addition to the many interdisciplinary possibilities available through regular graduate degree programs. GIDPs transcend departmental boundaries by facilitating cutting edge teaching and research at the nexus of traditional disciplines. The high value placed on interdisciplinary research and education is indicative of The University of Arizona's enthusiasm and commitment to fostering innovation and creativity among its faculty and students.
University of Arizona - Main - Tucson
Arizona Online - Online
For admission to the Graduate Certificate 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.
The certificate program does not required standardized tests.
We do not offer financial assistance for certificate students.
Domestic Applicants and Online International Applicants:
Main Campus International Applicants:
International applicants may be considered for conditional admission to this program at the department's discretion.
A minimum of 12 units of coursework (graded C or better) with a minimum GPA of 3.0 is required for the Graduate Certificate, made up as follows:
1. Core Statistical Theory Course; 3 units as follows:
STAT 566 – Theory of Statistics (available online)
2. Additional Elective Courses; minimum 9 units from any of the following:
ANS 513/GENE 513 – Statistical Genetics for Quantitative Measures
AREC 517/ECON 517 – Introductory Mathematical Statistics for Economists
BIOS 576B - Biostatistics for Research (available online)
BIOS 576C – Applied Biostatistics Analysis
BIOS 576D – Data Management and the SAS Programming Language
BIOS 647 – Analysis of Categorical Data, or
STAT 574C/SOC 574C – Categorical Data Analysis
BIOS 648 – Analysis of High Dimensional Data
BIOS 675 – Clinical Trials and Intervention Studies
BIOS 684 – General Linear and Mixed Effects Models, or
FSHD 617C – Advanced Data Analysis: Multilevel Modeling
BIOS 686 – Survival Analysis
BIOS 696S – Biostatistics Seminar*
ECE 639 – Detection and Estimation in Engineering Systems (available online)
ECOL 518 – Spatio-Temporal Ecology
ECON 518 – Introduction to Econometrics
ECON 520 – Theory of Quantitative Methods in Economics
ECON 522A – Econometrics, or
AREC 559 – Advanced Applied Econometrics
ECON 522B – Econometrics
ECON 549 – Applied Econometric Analysis
EDP 558 – Educational Tests and Measurements
EDP 646A – Multivariate Methods in Educational Research
EDP 658A – Theory of Measurement
EDP 658B – Theory of Measurement
FSHD 617A – Advanced Data Analysis: Structural Equation Modeling
FSHD 617B – Advanced Data Analysis: Dyadic Data Analysis
FSHD 617C – Advanced Data Analysis: Multilevel Modeling
GEOG 585A – Applied Time Series Analysis
or STAT 574T – Time Series Analysis
HWRS 655 – Stochastic Methods in Surface Hydrology
LING 539 – Statistical Natural Language Processing
LING 582 – Advanced Statistical Natural Language Processing
MATH 529 – Multivariate Analysis
MATH 543 – Theory of Graphs and Networks
MATH 565A – Stochastic Processes
MATH 565B – Stochastic Processes
MATH 565C – Stochastic Differential Equations
MATH 574M – Statistical Machine Learning
MATH 575A – Numerical Analysis
MATH 577 – Monte Carlo Methods
MCB 516A – Statistical Bioinformatics and Genomic Analysis
MGMT 582D – Multivariate Analysis in Management
MIS 545 – Data Mining for Business Intelligence (available online)
NURS 646 – Healthcare Informatics: Theory and Practice (available online)
OPTI 637 – Principles of Image Science
PHYS 528 – Statistical Mechanics
PLS 565 – Practical Skills for Next Generation Sequencing Data Analysis
PSY 507B – Statistical Methods in Psychological Research
PSY 507C – Research Design & Analysis of Variance
PSY 597G – Graphical Exploratory Data Analysis
RNR 520 – Advanced Geographic Information Systems
SIE 520 – Stochastic Modeling I (available online)
SIE 522 – Engineering Decision Making Under Uncertainty (available online)
SIE 525 – Queuing Theory (available online)
SIE 531 – Simulation Modeling and Analysis (available online)
SIE 536 – Experiment Design and Regression (available online)**
or STAT 571B – Design of Experiments (available online)
SIE 545 – Fundamentals of Optimization (available online)
SIE 606 – Advanced Quality Engineering (available online)
SOC 570B – Social Statistics
STAT 563 – Probability Math
STAT 564 – Theory of Probability (available online)
STAT 567A – Theoretical Statistics I
STAT 567B – Theoretical Statistics II
STAT 571A – Advanced Statistical Regression Analysis (available online)
STAT 571B – Design of Experiments (available online)
or SIE 536 – Experiment Design and Regression (available online)**
STAT 574B – Bayesian Statistical Theory and Applications
STAT 574C – Categorical Data Analysis
STAT 574E – Environmental Statistics
STAT 574G – Introduction to Geostatistics
STAT 574S – Survey Sampling
STAT 574T – Time Series Analysis
or GEOS 585A – Applied Time Series Analysis
STAT 579 – Spatial Statistics and Spatial Econometrics
STAT 675 – Statistical Computing
STAT 687 – Theory of Linear Models
STAT 688 – Statistical Consulting***
STAT 696E – Econometric Modeling I
*A maximum of 3 units of Biostatistics Seminar (BIOS 696S) may be applied towards the Elective Certificate/PhD Minor course requirements.
**If you plan to continue on to the Statistics MS or PhD programs at the University of Arizona, you must take STAT 571B, not SIE 536.
***A maximum of 3 units of Statistical Consulting (STAT 688) may be applied towards the Elective Certificate/PhD Minor course requirements.
Students may complete more of the courses listed in Core Coursework.
There are no additional requirements.
Please refer to the Graduate Student Handbook for students who are pursuing this program of study.