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Coursework by Degree - PhD

Click here for the complete list of courses, including course descriptions, prerequisites, and semesters offered.

Regular Track

A minimum of 71 units of coursework, with at least a 3.0 overall GPA, past the Bachelor’s Degree is required, made up as follows:

1.  Core PhD Courses; minimum 32 units as follows:

            15 units from the set of Core MS Statistics courses:

                        STAT 564/MATH 564 – Theory of Probability

                        STAT 566/MATH 566 – Theory of Statistics

                        STAT 571A/MATH 571A – Advanced Statistical Regression Analysis

                        STAT 571B/MATH 571B – Design of Experiments

                        STAT 688/ABE 688/CPH 688 – Statistical Consulting

(a maximum of 3 units of Statistical Consulting, STAT 688/ABE 688/CPH 688, may be applied towards the Core PhD course requirements) along with an additional set of 17 units of Core PhD Statistics courses:

                        MATH 523A – Real Analysis, or

                                    MATH 527B – Principles of Analysis

                        MATH 563/STAT 563 – Probability Theory

                        STAT 567A/MATH 567A – Theoretical Statistics

                        STAT 675 – Statistical Computing

                        STAT 687/CPH 687/EPID 687 – Theory of Linear Models

                        PHCL 595B – Scientific Writing Strategies, Skills & Ethics, or

                                    IMB 521 – Scientific Grantsmanship

 

2.  Additional Elective Courses; minimum 12 units from any of the following:

            AME 574 – Reliability and Quality Analysis

            ANS 513/GENE 513 – Statistical Genetics for Quantitative Measures

            CPH 576B/EPID 576B – Biostatistics for Research

            CPH 576C/EPID 576C – Applied Biostatistics Analysis

            CPH 576D/EPID 576D – Data Management and the SAS Programming Language

            CPH 647/EPID 647 – Analysis of Categorical Data, or

                        STAT 574C/SOC 574C – Categorical Data Analysis

            CPH 648/EPID 648 – Analysis of High Dimensional Data

            CPH 675/EPID 675– Clinical Trials and Intervention Studies

            CPH 684/EPID 684 – General Linear and Mixed Effects Models

CPH 685 – Fundamentals in Statistical Genetics and Genomics         

CPH 686/EPID 686 – Survival Analysis

            CPH 696S/EPID 696S – Biostatistics Seminar

            ECE 631 – Neural Networks

            ECE 639 – Detection and Estimation in Engineering Systems

            ECOL 518 – Spatio-Temporal Ecology

            ECON 522A – Econometrics, or

                        AREC 559 – Advanced Applied Econometrics

            ECON 522B – Econometrics

            ECON 549/AREC 549 – Applied Econometric Analysis

            EDP 548 – Statistical Packages in Research

            EDP 558 – Educational Tests and Measurements, or

                        PSY 507B – Statistical Methods in Psychological Research

            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 579/STAT 579/ ECON 579 – Spatial Statistics and Spatial Econometrics

            GEOS 585A – Applied Time Series Analysis

            INFO 510 – Bayesian Modeling and Inference

            INFO 521 – Introduction to Machine Learning

            LAW 611C – Litigating with Experts/ ECON 538 – Law and Economics

            LING 539 – Statistical Natural Language Processing

            LING 582– Advanced Statistical Natural Language Processing

            MATH 529 – Topics in Modern Analysis

            MATH 543 - Graph Theory            

            MATH 565A – Stochastic Processes

            MATH 565B – Stochastic Processes

            MATH 565C – Stochastic Differential Equations

            MATH 568 – Applied Stochastic Processes, or

                        HWR 655/C E 655 – Stochastic Methods in Surface Hydrology

            MATH 574M– Statistical Machine Learning

            MATH 575A/CSC 575A – Numerical Analysis

            MATH 579 – Game Theory and Mathematical Programming, or

                        SIE 543 – Game Theory

            MCB 516A/ABE 516A – Statistical Bioinformatics and Genomic Analysis

            MGMT 582D – Multivariate Analysis in Management

            OPTI 528 – Information and Noise in Quantum Optics and Photonics

            OPTI 637 – Principles of Image Science

            PHYS 528 – Statistical Mechanics

PLS 565 – Practical Skills for Next Generation Sequencing Data Analysis    

PSY 507C – Research Design & Analysis of Variance

            PSY 597G – Graphical Exploratory Data Analysis

            RNR 520/GEOG 520 – Advanced Geographic Information Systems

            SIE 520 – Stochastic Modeling I

            SIE 522 – Engineering Decision Making Under Uncertainty

            SIE 525 – Queuing Theory

            SIE 531 – Simulation Modeling and Analysis

            SIE 545 – Fundamentals of Optimization

            SIE 606 – Advanced Quality Engineering

            SOC 570B –Social Statistics

            STAT 567B/MATH 567B – Theoretical Statistics

            STAT 574B/ECON 574B – Bayesian Statistical Theory and Applications (Same as ECON 696E)

            STAT 574C/SOC 574C – Categorical Data Analysis, or

                        CPH 647/EPID 647 – Analysis of Categorical Data

            STAT 574E/MATH 574E/CPH 574E – Environmental Statistics

            STAT 574G/GEOG 574G/MATH 574G – Introduction to Geostatistics

            STAT 574S – Survey Sampling

            STAT 574T/MATH 574T – Time Series Analysis

            STAT 599 – Independent Study (requires form - see https://www.registrar.arizona.edu/forms.htm)

            STAT 900 – Research

A maximum of 6 units of Biostatistics Seminar (CPH 696S/EPID 696S) may be applied towards the Elective PhD course requirements.

3.  A minimum of 9 additional units for the PhD minor in one of the following areas:

            Applied Mathematics

            Biostatistics

            Computer Science

            Ecology and Evolutionary Biology

            Information Resources and Library Science

            Mathematics

Where needed to suit a particular or specialized need in an individual student’s program of study, petition may be made to the GIDP Executive Committee for approval of a UA minor not listed above to satisfy the minor requirement.  The student must be in good standing and must exhibit ongoing, satisfactory progress towards completion of the degree.  The burden of proof for admitting a commensurate, alternate minor rests with the student, and the decision of the committee will be final.

4.  Dissertation credit:  minimum 18 units of STAT 920

As per Graduate College requirements, a minimum of 18 units in the PhD program of study must include dissertation credits.  These are used to undertake the PhD research.  Registration for any units of STAT 920 is restricted to students who have assembled an active, complete PhD Comprehensive Examination Committee (see below).  Students who wish to undertake research coursework prior to assembling a Comprehensive Committee may consider STAT 599 and/or STAT 900 as possible alternatives; however, a maximum of only 6 units from STAT 599 and/or STAT 900 may be applied to the PhD program of study. A form is required for STAT 599.

Courses may be added to or removed from this list by action of the Statistics GIDP Curriculum Committee, after approval by the GIDP Executive Committee. See Program Handbook for more information.

 

 

Statistical Informatics Track

A minimum of 71 units of coursework, with at least a 3.0 overall GPA, past the Bachelor’s Degree is required, made up as follows:

1.  Core PhD Courses; minimum 23 units as follows:

            15 units from the set of Core MS Statistics courses:

                        STAT 564/MATH 564 – Theory of Probability

                        STAT 566/MATH 566 – Theory of Statistics

                        STAT 571A/MATH 571A – Advanced Statistical Regression Analysis

                        STAT 571B/MATH 571B – Design of Experiments

                        MATH 574M– Statistical Machine Learning

                        STAT 675 – Statistical Computing

                        STAT 688/ABE 688/CPH 688 – Statistical Consulting

(a maximum of 3 units of Statistical Consulting, STAT 688/ABE 688/CPH 688, may be applied towards the Core PhD course requirements) along with an additional set of 8 units of Core PhD Statistical Informatics courses:

                        PHCL 595B – Scientific Writing Strategies, Skills & Ethics, or

                                IMB 521 – Scientific Grantsmanship

 

2.  Additional Elective Courses; minimum 21 units.

Minimum 6 units from Theme (a) "General", with minimum 6 units from any other single "theme" (b)–(g), and any 9 additional units from the list below (no course can be used if it overlaps with a course required by the minor, above).  It is the student’s responsibility, prior to enrolling in any of the electives listed below, to complete any courses listed as prerequisites by the offering unit.

(a) General

            BIOS 648 – Analysis of High Dimensional Data

            BIOS 684 – General Linear and Mixed Effects Models

            INFO 510 – Bayesian Modeling and Inference

            STAT 574B/ECON 574 – Bayesian Statistical Theory and Applications (Same as ECON 696E)

            STAT 574C/SOC 574C – Categorical Data Analysis

            STAT 687/CPH 687/EPID 687 – Theory of Linear Models   

            MATH 529 – Topics in Modern Analysis

            MATH 575A/CSC 575A – Numerical Analysis

            MATH  575B/CSC 575B – Numerical Analysis II

            MATH 636/ECE 636 – Information Theory

            SIE 520 – Stochastic Modeling I

            SIE 545 – Fundamentals of Optimization

(b) Bioinformatics

            ECOL 553 – Functional and Evolutionary Genomics

            CSC 550 – Algorithms in Bioinformatics

            CSC 650 – Algorithms for Computational Biology

            INFO 554 – Informatics in Biology

            MCB 516A/ABE 516A – Statistical Bioinformatics and Genomic Analysis

            PLS 565 – Practical Skills for Next Generation Sequencing Data Analysis      

(c) Business & management informatics

            MIS 510 – Web Computing and Mining

            MIS 525 – Models for Decision Support

            MIS 545 – Data Mining for Business Intelligence  

            MIS 580 – Knowledge Management: Techniques and Practices

(d) Computing

            INFO 521 – Introduction to Machine Learning

            BIOS 576D – Data Management and the SAS Programming Language

            ECE 631 – Neural Networks

EDP 548 – Statistical Packages in Research

MATH 575A/CSC 575A – Numerical Analysis

            MATH  575B/CSC 575B – Numerical Analysis II

(e) Geographic information systems (GIS)

            STAT 574G/GEOG 574G – Introduction to Geostatistics

            GEOG 524 – Integrated Geographic Information Systems

            RNR 520/GEOG 520 – Advanced Geographic Information Systems

(f) Medical informatics

            MIS 518 – Biomedical and Security Informatics

            IRLS 646/NURS 646 – Healthcare Informatics: Theory and Practice

            BIOS 675 – Clinical Trials and Intervention Studies

            CPH 678 – Principles of Public Health Informatics (max. 3 units)

            PHPR 817 – Introduction to Informatics

(g) Specialized theme

Where needed to suit a particular or specialized need in an individual student’s program of study, petition may be made to the GIDP Executive Committee for approval of an alternate, tailored 6-15 unit Theme.  The student must be in good standing and must exhibit ongoing, satisfactory progress towards completion of the degree.  The burden of proof for admitting a commensurate, Specialized Theme rests with the student, and the decision of the committee will be final.

3.  A minimum of 9 additional units for the PhD minor in one of the following areas:

            Agricultural and Biosystems Engineering

            Applied Mathematics

            Biostatistics

            Computer Science

            Ecology and Evolutionary Biology

            Information Resources and Library Science

            Mathematics

Where needed to suit a particular or specialized need in an individual student’s program of study, petition may be made to the GIDP Executive Committee for approval of a UA minor not listed above to satisfy the minor requirement.  The student must be in good standing and must exhibit ongoing, satisfactory progress towards completion of the degree.  The burden of proof for admitting a commensurate, alternate minor rests with the student, and the decision of the committee will be final.

4.  Dissertation credit:  minimum 18 units of STAT 920

As per Graduate College requirements, a minimum of 18 units in the PhD program of study must include dissertation credits.  These are used to undertake the PhD research.  Registration for any units of STAT 920 is restricted to students who have assembled an active, complete PhD Comprehensive Examination Committee (see below).  Students who wish to undertake research coursework prior to assembling a Comprehensive Committee may consider STAT 599 and/or STAT 900 as possible alternatives; however, a maximum of only 6 units from STAT 599 and/or STAT 900 may be applied to the PhD program of study. A form is required for STAT 599.

Courses may be added to or removed from this list by action of the Statistics GIDP Curriculum Committee, after approval by the GIDP Executive Committee. See Program Handbook for more information.

Last updated 11 Aug 2017