A minimum of** 62 units of coursework, plus minor units **(usually 9 – 12 units depending on the rules for your minor), with at least a 3.0 overall GPA, past the Bachelor’s Degree is required, made up as follows:

**PhD Major Coursework - 62 units**

**18 units from the set of the following Core 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 - Machine Learning
- STAT 688A and STAT 688B/ABE 688/BIOS 688 – Statistical Consulting

- MATH 523A – Real Analysis, or
- MATH 527B – Principles of Analysis
- STAT 567A/MATH 567A – Theoretical Statistics I
- STAT 675 – Statistical Computing
- STAT 687/BIOS 687/EPID 687 – Theory of Linear Models
- PHCL 595B – Scientific Writing Presentation and Bio Ethics, or
- IMB 521 – Scientific Grantsmanship

- GENE 513 – Statistical Genetics for Quantitative Measures
- BIOS 576B– Biostatistics for Research
- 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
- BIOS 685 – Special Topics in Biostatistics – needs prior approval, depends on topic
- BIOS 686– Survival Analysis
- BIOS 696S– Biostatistics Seminar
- 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 Package for 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
- LING 539 – Statistical Natural Language Processing
- LING 582– Advanced Statistical Natural Language Processing
- MATH 529 – Topics in Modern Analysis
- MATH 543 - Theory of Graphs and Networks
- MATH 563/STAT 563 – Probability Math
- MATH 565A – Stochastic Processes
- MATH 565B – Stochastic Processes
- MATH 565C – Stochastic Differential Equations
- MATH 568 – Applied Stochastic Processes, or
- HWRS 655/C E 655 – Stochastic Methods in Surface Hydrology
- MATH/STAT 574M– Statistical Machine Learning
- MATH 575A/CSC 575A – Numerical Analysis
- MCB 516A/ABE 516A – Statistical Bioinformatics and Genomic Analysis
- MGMT 582D – Multivariate Analysis in Management
- OPTI 528 – Adaptive Optics and Imaging Through Random Media
- 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 II
- STAT 574B/ECON 574B – Bayesian Statistical Theory and Applications (Same as ECON 696E)
- STAT 574C/SOC 574C – Categorical Data Analysis, or
- BIOS 647/EPID 647 – Analysis of Categorical Data
- STAT 574E/MATH 574E/BIOS 574E – Environmental Statistics
- STAT 574G/GEOG 574G/MATH 574G – Introduction to Geostatistics
- STAT 574S – Survey Sampling
- STAT 574T/MATH 574T – Time Series Analysis
- STAT/MATH 574M - Machine Learning
- STAT 599 – Independent Study (requires form)
- STAT 900 – Research

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

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.

**PhD Minor Coursework**

Once a minor is chosen the student must check with the minor department to determine the required coursework and number of units. Some minors require 9 units and some minors require 12 or more units.

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.

Extra Info

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.

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