Coursework Requirements for Ph.D. Minor and Graduate Certificate in Statistics & Data Science

Complete list of courses, including course descriptions, prerequisites, and semesters offered.

 

A minimum of 12 units of coursework (graded B or better) are required for the Minor and the Certificate (options are listed below).  Please note, students who do not receive a B or better grade for their minor coursework may instead have an overall 3.0 GPA for minor coursework & pass the qualifying exam, theory version, at the MS level.  In any case a B is required for STAT 566 or the student must pass the theory portion of the Qualifying Exam with at least a MS Pass.

1.  Core Statistical Theory Course; 3 units as follows:

            STAT 566 – Theory of Statistics (available online) - A minimum grade of B is required.

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
  • BOS 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*
  •  CSC 580 Principles of Machine Learning
  •  ECE 523 Engineering Applications of Machine Learning and Data Analytics
  •  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
  •    INFO 521 - Introduction to Machine Learning
  •    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.

 

Changes to the PhD Minor in Statistics

Where needed to suit a particular or specialized need in an individual student’s curriculum plan, petition may be made to the GIDP Executive Committee through the GIDP Chair for approval of a course not listed above for use as an Elective Course.  The decision of the committee will be final.  In no case, however, will a prerequisite course for any Elective Course be considered for such special approval if it is not already listed as an approved course, nor may a course be used to satisfy both a major degree requirement and a requirement for the PhD Minor in Statistics.