**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.*