Graduate Student Handbook

Appendix 1.  GIDP Faculty & Research Interests

1. Regular Members

Regular Members of the GDIP in Statistics are those University faculty and staff involved in teaching core Statistics courses, directing M.S. and Ph.D. students in the GIDP, and/or others who have agreed to be significantly active in the Program.

Mark S. Aldenderfer, Ph.D. (Pennsylvania State University), Professor of Anthropology.
Applied multivariate analysis; Spatial statistics;  Cluster analysis.

Jacobus J. (Kobus) Barnard, Ph.D. (Simon Fraser University), Assistant Professor of Computing Science; Assistant Professor of Electrical and Computer Engineering.
Machine learning; Mathematical modeling of geometric form; Multi-modal data; Statistical applications in computer vision.

Katherine Y. Barnes, Ph.D. (University of Minnesota), J.D. (University of Michigan), Associate Professor of Law; Director, Rogers Program on Law and Society.
Bayesian statistics; Causation and selection models; Empirical methods in law; Discrimination; Expert witnesses.

Rabindra N. (Rabi) Bhattacharya, Ph.D. (University of Chicago), Professor of Mathematics.
Markov processes; Large sample theory; Statistical shape analysis; Economic theory of growth under uncertainty.

Zhao Chen, Ph.D. (University of Arizona), Associate Professor of Public Health.
Research study design; Longitudinal data analysis; Risk assessment.

Peter Chesson, Ph.D. (University of Adelaide, Australia), Professor of Ecology & Evolutionary Biology.
Mathematical ecology; Ecological statistics; Stochastic processes; Biodiversity.

Melinda F. (Mende) Davis, Ph.D. (University of Arizona), Research Assistant Professor of Pediatrics; Assistant Professor of Public Health.
Latent variable modeling; Measurement of change; Item response theory; Health outcomes research; Statistical consulting.

Michael N. Evans, Ph.D (Columbia University), Associate Professor of Dendrochronology; Associate Professor of Geosciences; Associate Professor of Atmospheric Sciences.
Paleoclimatology; Spatiotemporal data analysis; Forward and inverse modeling.

William G. Faris, Ph.D. (Princeton University), Professor of Mathematics.
Stochastic processes; Mathematical statistics.

Chiu-Hsieh (Paul) Hsu, Ph.D. (University of Michigan), Assistant Professor of Public Health.
Survival analysis; Missing data; Statistical modeling.

Alfonso Flores-Lagunes, Ph.D. (Ohio State University), Assistant Professor of Economics.
Spatial statistics; Causal inference; Simulation methods; Econometrics.

Sylvan B. Green, M.D. (University of Pennsylvania); Professor of Public Health; Director of Biometry, Arizona Cancer Center; Linda McCartney Breast Cancer Chair in Biometry.
Biostatistics; Epidemiologic studies; Clinical trials and prevention trials.

Keisuke Hirano, Ph.D. (Harvard University), Associate Professor of Economics.
Econometrics; Causal inference.

Alan P. Ker, Ph.D. (North Carolina State University), Professor of Agricultural Resource Economics; Professor of Economics; Head, Department of Agricultural Resource Economics.
Nonparametric regression; Empirical Bayes methods; Nonparametric kernel density estimation.

Nirav Merchant, M.S. (University of Arizona), Director of Information Technology, Arizona Research Labs.
Data Mining; Classification; Quality Control.

Walter W. Piegorsch, Ph.D. (Cornell University), Professor of Mathematics; Professor of Public Health; Chair, GIDP in Statistics.
Environmental statistics; Quantitative Risk Assessment; Biometry; History of statistics.

James Ranger-Moore, Ph.D. (Cornell University), Associate Professor of Public Health; Director, Division of Epidemiology & Biostatistics.
Simulation methods; Longitudinal analysis; Classification algorithms, Image analysis.

Denise J. Roe, Dr.P.H. (University of California at Los Angeles), Professor of Public Health.
Clinical trials; Epidemiological studies; Pharmacokinetics.

Moshe Shaked, Ph.D. (University of Rochester), Professor of Mathematics.
Reliability theory; Stochastic modeling; Stochastic orders.

Duane L. Sherrill, Ph.D. (University of Colorado Health Sciences Center), Professor of Public Health; Associate Dean of Research, Mel and Enid Zuckerman College of Public Health.
Longitudinal analyses; Respiratory disease assessment; Applied data analyses; Biometry.

Robert J. Steidl, Ph.D. (Oregon State University), Associate Professor of Natural Resources. 
Quantitative ecology; Dynamics of animal populations; Conservation biology.

Michael Tabor, Ph.D. (Imperial College), Professor of Applied Mathematics; Professor of Physics; Professor of Mathematics; Head, GIDP in Applied Mathematics.
Nonlinear growth dynamics; Chaotic dynamical systems; Biomechanical models; Biomathematics.

Daoqin Tong, Ph.D. (Ohio State University), Assistant Professor of Geography & Regional Development.
Spatial statistics; Optimization; Geographic information systems (GIS).

Bruce Walsh, Ph.D. (University of Washington), Professor of Ecology & Evolutionary Biology; Adjunct Professor of Plant Science; Adjunct Professor of Animal Science; Adjunct Professor of Molecular and Cellular Biology; Adjunct Professor of Public Health.
Biostatistics; Statistical genetics/genomics; Mixed models; Bayesian analysis; Resampling and MCMC methods.

Joseph C. Watkins, Ph.D. (University of Wisconsin), Associate Professor of Mathematics.
Stochastic processes; Limit theorems; Statistical applications in the life sciences.

Affiliate Members of the GDIP in Statistics are those with a general interest in statistical issues who wish to be fully informed of the Program’s operation, and who wish to engage in a limited subset of Program activities.  Affiliate members often rotate to Regular status at pertinent intervals, and vice versa.

Ronald L. Breiger, Ph.D. (Harvard University), Professor of Sociology.
Statistical models for social network analysis; Log-linear models; Log-multiplicative models for contingency tables.

Emily A. Butler, Ph.D. (Stanford University), Assistant Professor of Family Studies & Human Development.
Multivariate time-series analysis; Multilevel modeling; Dyadic models; Social-relations modeling.

Noel A. Card, Ph.D. (St. John's University), Assistant Professor of Family Studies & Human Development.
Latent variable modeling; Structural equation modeling; Meta-analysis; Dyadic data analysis.

John J. Cheslock, Ph.D. (Cornell University), Assistant Professor of Higher Education.
Applied econometrics; Analysis of panel data.

Andrew C. Comrie, Ph.D. (Pennsylvania State University), Professor of Geography & Regional Development; Associate Vice President for Research; Dean of the Graduate College and Director of Graduate Interdisciplinary Programs.
Statistics of climate data; Data reduction; Spatial modeling.

Sandy Dall'erba, Ph.D. (University of Pau), Assistant Professor of Geography & Regional Development.
Spatial statistics; Spatial econometrics.

Jonah B. Gelbach, Ph.D. (Massachusetts Institute of Technology), Associate Professor of Economics.
Applied microeconometrics; Bootstrap-based inference; Public economics; Law and economics.

Gautam Gowrisankaran, Ph.D. (Yale University), Associate Professor of Economics.
Structural econometric modeling; Applied Bayesian econometrics; Estimation of dynamic models.

James T. (Jake) Harwood, Ph.D. (University of California at Santa Barbara), Professor of Communication.
Applied statistics in the social sciences; Hypothesis testing; Moderator and mediator effects.

Robert S. Maier, Ph.D. (Rutgers University), Professor of Mathematics.
Applied probability; Mathematical statistics; Limit laws and large deviation theory; Bioinformatics.

Joanna Masel, D.Phil. (Oxford University), Assistant Professor of Ecology & Evolutionary Biology.
Markov chains; Bayesian learning models; Biometry.

Chris Segrin, Ph.D. (University of Wisconsin), Professor of Communication; Professor of Psychology; Professor of Family Studies; Head, Department of Communication.
Meta-analysis; Longitudinal data analysis; Regression analysis; Dyadic data analysis.

Appendix 2.  Independent Study Enrollment Form

Independent study via STAT 599 (1-3 units) is considered by the University as an individual studies course, and must be approved in advance with the responsible faculty member who has agreed to supervise the work.  STAT 599 may be repeated for credit up to a maximum of 6 units.  An Independent Study Proposal Form must be submitted to the GIDP Office.  The form allows students and instructors to document expectations for independent study or directed research credit.  It is available online from the University, or from the GIDP office.

Appendix 3.  Material Covered in the Ph.D. Qualifying Examination

To proceed towards Ph.D. candidacy in the GIDP, a student must pass a written Ph.D. Qualifying Examination by the beginning of her/his fourth semester of study.  The examination may be retaken only once.  Offered during May and January of each year, the Qualifying Examination is used to assess the student’s potential to successfully complete a Ph.D. dissertation in modern interdisciplinary statistics.  It tests the student’s ability to integrate material from the following core Ph.D. courses, and to use this knowledge in solving pertinent, challenging statistical problems commensurate with Ph.D. status at the level of these courses:

STAT 564/MATH 564 -- Theory of Probability  (3 units)
Description:  Probability spaces, random variables, weak law of large numbers, central limit theorem, various discrete and continuous probability distributions. Graduate-level requirements include more extensive problem sets or advanced projects.

STAT 566/MATH 566 -- Theory of Statistics  (3 units)
Description:  Sampling theory. Point estimation. Limiting distributions. Testing Hypotheses. Confidence intervals. Large sample methods. Graduate-level requirements include more extensive problem sets or advanced projects.

STAT 571A/MATH 571A -- Advanced Statistical Regression Analysis (3 units)
Description:  Regression analysis including simple linear regression and multiple linear regression.  Matrix formulation and analysis of variance for regression models. Residual analysis, transformations, regression diagnostics, multicollinearity, variable selection techniques, and response surfaces.  Students will be expected to utilize standard statistical software packages for computational purposes.

STAT 571B/MATH 571B -- Design of Experiments (3 units)
Description:  Principles of designing experiments. Randomization, block designs, factorial experiments, analysis of contrasts, multiple comparisons, analysis of variance and covariance, repeated measures, variance components analysis.  Students will be expected to utilize standard statistical software packages for computational purposes.
--OR--
PSYC 507C -- Research Design & Analysis of Variance  (3 units)
Description:  This course provides an overview of research design and statistical analysis with a special focus on Analysis of Variance. Various designs including between subjects, repeated measures, mixed, hierarchical and Latin Square designs are covered. Other topics addressed are contrasts among means and trends analysis.

Each specific Qualifying Examination is constructed and graded by a committee of GIDP faculty appointed annually by the GIDP Chair.  Where possible, this will include the instructors of the pertinent core courses.  A minimum of two examiners grade every question independently.

Appendix 4.  Potential Ph.D. Minors

Possible Ph.D. Minors for students in the Statistics GIDP include the following.  This list is not considered exhaustive, and students should study the Graduate College Catalog for other possible Minor areas that can meet their individual interdisciplinary interests.

The Ph.D. Minor in Agricultural Resource Economics (AREC) requires a total of 12 units in AREC courses.  Two of the following Core Courses are required (6 units total):
Production Economics (AREC 504) [3 units]
Consumption Economics and Price Analysis (AREC 513) [3 units]
Introduction to Econometrics (ECON 518) [3 units]
Applied Econometric Analysis (ECON 549) [3 units]
One of the two Core Courses must be either AREC 504 or AREC 513.  The Ph.D. core courses ECON 501A, ECON 501B, and ECON 522A can be substituted for AREC 504, AREC513, and AREC 549, respectively. 

Next, 6 units should be chosen from the following AREC Specialty Courses (and/or from the remaining core courses):
Economic Policy in Developing Countries (AREC 521) [3 units]
Cost-Benefit Analysis (AREC 514) [3 units]
Operations Research in Applied Economics (AREC 515) [3 units]
Agricultural Development (AREC 516) [3 units]
Introductory Mathematical Statistics for Economists (AREC 517) [3 units]
Financial Management for Agribusiness (AREC 550) [3 units]
Advanced Applied Econometrics (AREC559) [4 units]
Economics of Natural Resource Policy (AREC 575) [3 units]
Advanced Natural Resource Economics (AREC576) [3 units]
Advanced Topics in the Economics of Environmental Regulation (AREC 577) [3 units]
Mathematics for Economists (AREC 580) [2 units]

In no case may a student receive credit for the Ph.D. Minor in Agricultural and Resource Economics based on coursework used to satisfy requirements for an M.S. degree in Agricultural and Resource Economics or an M.S. or Ph.D. degree in Statistics.

Doctoral students who elect a Minor in Anthropology must complete 12 hours of graduate coursework (15 hours for Medical Anthropology).  Students interested in the Minor should consult with the Graduate Advisor in Anthropology to develop an appropriate plan of study.

In order to receive an Applied Mathematics Minor, the student must take four (4) 500-level MATH courses (12 units) and maintain a better than 3.0 GPA for these classes.  At least 3 of these units must be from the Applied Mathematics core sequence as listed below:
•      MATH 527A, 527B: Principles of Analysis (3 credit hours per semester)
•      MATH 575A, 575B: Numerical Analysis (3 credit hours per semester)
•      MATH 583A, 583B: Principles & Methods in Applied Mathematics (3 credit hrs per semester)
The other MATH courses should not be cross-listed with a 400-level course.  The complete course list chosen must be specified on the Minor application form and submitted for approval to the Applied Mathematics Office in room 412 of the Math building.  By the student’s Oral Comprehensive Exam, a signature is required from the Head of the Program in Applied Mathematics.  At that time the GPA is verified.  Once the Oral Comprehensive paperwork is submitted to the Graduate College, the minor will be officially listed on the student’s transcript.  A student may not receive credit for the Ph.D. Minor in Applied Mathematics based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

Ph.D. students who wish to minor in Atmospheric Sciences must arrange with the Graduate Advisor in Atmospheric Sciences to select a 2-member Minor Committee.  Coursework involves at least 12 units of atmospheric sciences (ATMO) at the 500 level or higher.  Nine of these units, comprising the core courses, are to be selected from ATMO 541A/541B and ATMO 551A/551B.  Students must complete a written Minor exam covering the same 3 core courses.  The written examination may be waived by the student’s Minor Committee if grades of A or B are obtained in the required 3 core courses.

The Ph.D. minor in Biomedical Engineering (BME) consists of 12 units of approved BME courses, including 9 units from BME 510, BME 511, BME 516 or BME 517, and in addition 3 units of BME 597 (not including BME 597X).  The student’s dissertation committee should contain two faculty members in the BME Program.  The minor will be granted upon completion of these courses with a B average for the required units.  A Minor Program of Study form must be completed and a signed copy filed with the BME Program Committee.

The Ph.D. minor in Biostatistics consists of 12 units of approved courses, as follows: EPID 576c/CPH 576c, EPID 675/CPH 675, EPID 684/CPH 684, EPID 685/CPH 685, and EPID 686/CPH 686. A student may not receive credit for the Ph.D. Minor in Biostatistics based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

Doctoral students seeking a Minor in Computer Science (CSC) must apply for admission to the minor. The admission process is used to ensure that students are qualified to undertake graduate-level courses in Computer Science.  Prospective Minors are required to have undergraduate preparation in computing necessary to attempt first-year graduate courses in the department.  A well-prepared applicant should be proficient in a high-level programming language such as C or C++, and have a solid background in the following areas: (1) mathematics, including calculus and discrete mathematics; (2) machine architecture; (3) programming languages, including exposure to high-level languages (e.g., Java, LISP, Icon); (4) data structures; (5) algorithm analysis; (6) theory of computation; and (7) software systems, including compilers and operating systems.  Applicants lacking preparation in one or two of these areas may qualify for the minor with the stipulation that they remedy these deficiencies, if such missing background would be prerequisite for courses in their proposed minor program.  Deficiencies are normally remedied by auditing undergraduate courses in the department.

The student should consult the Ph.D. minor Faculty Advisor in Computer Science, Dr. Bongki Moon, regarding admissions requirements and a proposed minor program of studies prior to enrolling in courses or applying to the minor. To begin the admission process, complete the form PhD Minor Application for Admission/Qualification (PDF, also available in the Computer Science Department Academic Office).

Decisions on admission to the minor are made by the departmental Graduate Admissions Committee. A student who has been admitted and who has completed any deficiency courses designated by the Admissions Committee is considered to have passed the minor Qualifying Examination in Computer Science, and the Qualifying Examination is waived.

Course Requirements for the Minor consist of 12  units of CSC courses, at least 9 of which must be from courses among the Comprehensive Examination Core Topics in systems (CSC 452, 552, 553 and 576), theory (CSC 473, 520, 545 and 573) and applications (CSC 522, 525, 533, and 560).  The remaining 3 units are from unrestricted Computer Science electives.  More advanced courses can be substituted for courses covering the Comprehensive Exam Core Topics, if the student is adequately prepared for examination in three of the core course areas tested in the Minor Written Comprehensive Exam (see below).  The Graduate College permits at most six units of 400-level courses to be part of the degree program in the minor.  A letter grade of A or B must be earned in all minor courses.

Minors participate in Computer Science graduate Qualifying, Comprehensive, and Final examinations.  The Qualifying Examination in Computer Science is automatically waived provided a student has been admitted to the minor and has removed any admission deficiencies.  The Comprehensive Examination has written and oral components in both the major and minor fields of study; it is taken when essentially all course work has been completed.  The Minor Written Comprehensive Examination is given as a colloquium requirement (CSC 695B) to be taken during the last semester of minor coursework or the semester immediately following completion of the minor coursework.  The student must attend five research colloquia held in the Department of Computer Science to successfully pass this class.  CSC 695B must be completed prior to completion of the Oral Comprehensive Exam in both the minor and major subjects.  Doctoral Minors are required to successfully answer questions based upon both core and elective courses in their minor program of study.  The Oral Comprehensive Examination must take place within two regular terms following completion of the written prelims in the major and minor. It is administered by the student's doctoral committee, consisting of faculty from both the student's major and minor.

The Ph.D. Minor in Economics requires 15 units of study, via ECON 501A, ECON 501B, ECON 501C, ECON 520, and ECON 522A.  Students must also pass the first year written qualifying examination administered by the Department of Economics faculty.

A student may not receive credit for the Ph.D. Minor in Economics based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

A student obtaining a minor in Educational Psychology (EDP) will take a set of four courses (with a maximum of 3 units allowed in either EDP 599 or EDP 699) as determined by the minor advisor, a tenured or tenure-track faculty member in the Department of Educational Psychology.  The Graduate College requires a written examination in the ‘subject’ that is represented by the set of four courses prior to the student sitting for the Oral Comprehensive Examination, but there is no expectation that the minor advisor or any other from the faculty of the Department of Educational Psychology be a member of that oral examining committee.

There are several options for the written minor in EDP, and the advisor has the freedom to suggest an additional option that better fits a particular situation.  The advisor will involve at least one additional department faculty member for assistance in asking questions and grading answers.  Options include but are not limited to:  (1) answering questions in a 4-hour session, (2) a take-home assignment to substitute for the above, (3) a paper discussing how the minor subject contributes to the student’s major field.  (Note that the subject of the minor does not need to be totally contained within EDP and thus testing over all the ‘courses’ taken in the subject is not required.)

The Ph.D. minor in Epidemiology is designed for individuals who wish to obtain graduate training in Epidemiology.  It requires completion of the first year Epidemiology and Biostatistics courses, 2 additional Epidemiology elective courses, 1 year of Epidemiology Seminar, and completion of the qualifying examination.  For more information contact Ms. Amy Glicken, Recruitment and Admissions Coordinator.

The Ph.D. Minor in Finance requires 12 units of study, as follows:
•      Theory of Finance (FIN 600), and either
•      Three additional Ph.D. courses, including FIN 602, FIN 695A, and FIN 696E, or
•      Any two of FIN 602, FIN 695A, and FIN 696E, and one 500-level finance class.  The 500-level class may be based on the student’s interests, but is dependent on seating availability.  The recommended option is FIN 542.
A minimum grade of B is required in all courses taken for the Minor.  Students without any background in Finance are required to take FIN 510 before registering for any other Minor courses.  Registration for FIN 510 is controlled by the Eller College MBA office; the student and the Department of Finance Graduate Coordinator must request prior approval from the MBA office for the student to register in FIN 510.

Ph.D. students minoring in Genetics (GENE) are required to take 9-10 units as follows:
1.    GENE 546/MCB 546, Advanced Genetics (4 units), or
       PL S 528R, Microbial Genetics (3 units)
2.    GENE 568/MCB 568, Nucleic Acids (4 units)     
3.    GENE 522, History of Genetics (2 units)
In addition, a weekly seminar series (GENE 670, Recent Advances in Genetics) can be used to complement the classroom learning experience.  A student may not receive credit for the Ph.D. Minor in Genetics based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

Students who elect a Ph.D. minor in Geography must complete a minimum of 12 units of coursework in geography, including one core course (GEOG 500, GEOG 689, or an advanced methods course), with a maximum of 3 units of independent studies (GEOG 599 or GEOG 699).  The course work must be pre-approved by the Geography Director of Graduate Studies.  Students considering the Minor in geography should consult the Director of Graduate Studies and any potential committee members at an early date.

The Ph.D. Minor in Global Change (GC) provides a broad environmental and earth system science perspective.  The Minor requires 12 units of coursework (B grade or better), from which 9 units represent the GC required core courses,
GC 572 (3 credits) -- Global Biogeochemical Cycles
GC 530 (3 credits) -- The Climate System
GC 597A (3 credits) -- Global Change Workshop
and  the remaining 3 units are selected from a list of electives with approval of the Ph.D. Minor Faculty on the student’s committee (see below).  The elective list is as follows:

I. Global Energy and Water Cycles
ATMO 541A (3 units) -- Dynamic Meteorology
ATMO 551A (3 units) -- Introduction to Physical Meteorology
ATMO 595B/GEOS 595B/HWR 595B (3 units) -- Global Climate Change
ATMO 595C/ GEOS 595C/HWR 595C (1-3 units) -- General Circulation Observations & Modeling
GEOG 531 (3 units) -- Global and Regional Climatology
HWR 524 (3 units) -- Hydroclimatology

II. Biogeochemical Phenomena
ATMO 569A/ CHEE 569A (3 units) -- Air Pollution I
ATMO 569B/ CHEE 569B (3 units) -- Air Pollution II
GEOS 530 (3 units) -- Chemical Evolution of the Earth
GEOS 588 (3 units) -- Soil Geochemistry

III. Tools for Observing Earth
GEOG 516A (3 units) -- GIS for Geography and Regional Development
REM 590 (3 units) -- Remote Sensing for the Study of Planet Earth
RNR 517 (3 units) -- GIS for Natural Resources
RNR 519 (3 units) -- Cartographic Modeling for Natural Resources
SWES 553 (3 units) -- Remote Sensing of the Environment

IV. Past and Present Earth System
GEOS 562 (3 units) -- Introduction to Quaternary Ecology
GEOS 582 (3 units) -- Paleoclimatology
GEOS 595E (3 units) -- Dendroclimatology Colloquium

V. Human Dimensions
ANTH/ARL/LAS 631 (3 units) -- Anthropology and Development
POL/HWR/RNR 581 (3 units) -- Environmental Policy
GEOG 561 (3 units) -- Resource Management

Students who have previously taken one or more of the GC core classes to satisfy other Ph.D. requirements must consult a member of their Ph.D. Minor Faculty to identify appropriate substitute courses from the list of electives, and to receive formal approval from the minor representative(s). This arrangement is then formalized by a letter from the minor representative(s) to the GC Executive Committee.  A student may not receive credit for the Ph.D. Minor in Global Change based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

Students should identify and contact two GC faculty members to serve as minor representatives on their preliminary examination and final dissertation defense committees.  These faculty should be identified early in the student’s program, so they can serve as resources during the student’s studies.

The Ph.D. Minor in Management Information Systems (MIS) requires 12 units of MIS graduate courses (500-level or above) that will create a solid foundation in a particular area of MIS.  At least two of the courses must be chosen from the following list:
MIS 507B -- Data Communications
MIS 531A -- Data Structures and Algorithms
MIS 531B -- Data Structures and Database Management
MIS 541A -- Information Systems Analysis and Design
MIS 696D -- Models for Quantitative Analysis

Students interested in the Minor should contact an MIS faculty member and arrange to meet, in order to (i) obtain the member’s approval to serve as the Minor advisor, (ii) use the member’s expertise to help select appropriate graduate-level courses and make decisions regarding any additional requirements for the  Minor (including the Minor Preliminary Exam in reference to any specific requirements of the GIDP in Statistics), and (iii) obtain the member’s signature on the documents required by the GIDP in Statistics.

To minor in Mathematics a student is required to take four (4) approved graduate level MATH courses and complete a written examination which covers the content of those courses.  For more information see Professor William G. Faris.

Doctoral students majoring in other disciplines may elect a minor in Optical Sciences.  Such students must complete, for the full minor, 12 units of course work with a grade of B or better in optical sciences.  No more than 3 of these units may be cross-listed with the student's major department or program.  For a split minor, 6 units of course work with a grade of B or better is required.  In addition, students wishing to minor in Optical Sciences must complete the Written Comprehensive Exam, which is offered each semester.

Graduate students may obtain credit for a minor in Planetary Sciences by achieving a grade-point average of 3.0 or higher in a minimum of 12 units of 500-level planetary sciences courses (up to 3 units of which may be independent study supervised by a planetary sciences faculty member).  The proposed curriculum of each student must be approved by a minor committee established by the student in consultation with the department Graduate Admissions and Advising Committee, which will also designate a chair.  The written comprehensive examination will consist of the final examinations or the equivalent in the individual courses.

The Ph.D. minor in Systems and Industrial Engineering (SIE) consists of 12 units of regular SIE graduate coursework.  A minor that is split between SIE and another department requires 6 units of regular SIE course work.  A student may not receive credit for the Ph.D. Minor in Systems and Industrial Engineering based on coursework used to satisfy requirements for an M.S. or Ph.D. in Statistics, unless the course is required by both programs.

In consultation with the student’s advisor, the student forms a “minor” committee consisting of two SIE faculty members.  These individuals assist the student and the major advisor in developing and coordinating the student’s minor program of study consistent with her/his educational and career goals.  The format of the written portion of the preliminary examination is at the discretion of the minor committee members.

Students intending to minor in SIE should contact the Chair of the SIE Graduate Studies Committee at the earliest possible date.  Courses taken to satisfy the requirements for a PhD minor in SIE are subject to the approval of the SIE Graduate Studies Committee.

This handbook is dated: 9 August 2007.