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الثلاثاء، 22 نوفمبر 2016

Ph.D. Program in Statistics

Version: 2015-16. PDF, 32 pages.
The Ph.D. degree includes a thorough background of coursework in contemporary statistical theory, and provides an opportunity for studying a field in which statistics is applied.

Admission Requirements

An undergraduate major in mathematics or statistics is typical for statistics graduate students, but is not required. However, because of the mathematical nature of some of the graduate coursework, students should be able to demonstrate good mathematical ability. The minimal background for entrance into the graduate program is: a bachelor's degree with 3.0 overall grade-point average; facility with a programming language; and upper division work in mathematics and/or statistics; at least one semester or two quarters of advanced calculus at a level equivalent to Mathematics 25 and Mathematics 125A; and a quarter of linear algebra at a level equivalent to Mathematics 67. The program does not accept part-time students.
For more information on admissions requirements, please see our Admissions Section.

Program of Study

This is a Plan A program with final oral examination (defense of the dissertation). A Ph.D. student will select an area of specialization and will choose a major professor and dissertation adviser in that area, usually in the second or third year of study. The student's program of study will be developed by the student jointly with the Graduate Adviser.

Course Requirements for the Ph.D. degree:

Required Courses (34 units total):
  • Mathematical Statistics: Statistics 231A-231B-231C (4 units each)
  • Applied Statistics: Statistics 232A-232B-232C (4 units each)
  • Statistical Programming: Statistics 242 or Computational Statistics: Statistics 243 (4 units)
  • Seminar in Statistics: Statistics 290 (1 unit, three quarters, graded S/U)
  • Methods in Teaching Statistics: Statistics 390 (2 units, once, at the first offering of the course during residence, graded S/U)
  • Methods in Statistical Consulting: Statistics 260 (3 units, taken twice during program)
Elective Courses (18 units total):
In addition, five elective graduate courses (at least 18 units total), out of which at least four must be from Statistics.
Summary:
All coursework (a total of at least 52 units: 34 required and 18 elective units) and the program of study must be approved by the Graduate Adviser.

Ph.D. Pre-Qualifying Written Examination

The Ph.D. Pre-qualifying Written Examination will be given at the beginning of each Spring Quarter and also at the beginning of each Fall Quarter. Students in the Ph.D. program must attempt the exam in the Spring Quarter immediately after they complete both the STA 231AB and STA 232AB core course series. If a student does not attempt the examination at this time, it will be recorded as a ‘no pass’. Every Ph.D. student needs to pass the examination in a maximum of two attempts. If a student does not pass either the STA 231AB part or the STA 232AB part (or both) at the first attempt, the second attempt must take place at the next time the examination is offered. On the second attempt a stduent is only required to take the part that was not passed the first time. If a student does not attempt the exam at that time, it will be counted as a failure. Two ‘not passes’ of the examination will result in a recommendation to the Dean of Graduate Studies for discontinuation of the student in the Ph.D. program.
The Ph.D. Pre-qualifying Written Examination is a written exam with two parts: a theoretical part and an applied part. The duration of each part is about 3-4 hours. The applied part may be administered in a computer lab and may include the use of statistical software. The Chair of the Graduate Program in Statistics (GPS) will appoint an examination committee that will be responsible for preparing, administering and grading the examination. This committee will forward its recommendation to the GPS, which will make the final decision on each student.

Ph.D. Qualifying Examination

The Ph.D. Qualifying Examination is an oral exam. The exam will be attempted as soon as the Ph.D. Pre-qualifying Written Examination has been passed and all required coursework for the Ph.D. degree in Statistics has been completed. In accordance with university rules, students are requested to take their qualifying examination before the end of the third year to remain eligible for academic appointments such as TA. The preparation for the exam will be done by working closely with a faculty mentor (independent study). The Ph.D. Qualifying Examination covers a special research topic assigned by an examining committee consisting of five faculty members. A forty-five minute presentation given by the student is followed by a question period which covers the special research topic as well as coursework in general. The examining committee will be appointed by Graduate Council at the recommendation of the graduate adviser who consults with the student prior to making the recommendation. The major professor is not eligible to serve as chair of the examining committee.
Graduate Studies guidelines for Ph.D. Qualifying Examinations apply. These can be obtained from the Graduate Studies Website.
Title and abstract of the Ph.D. Qualifying Exam presentation will be distributed to all faculty and students of the Graduate Program in Statistics, who are invited to attend the presentation. A student who passes the Ph.D. Qualifying Examination is eligible for Advancement to Candidacy for the Ph.D. degree. The student must file the Plan A Candidacy form with the Office of Graduate Studies and pay the candidacy fee at the Cashier’s Office, to be promoted to Candidacy for the Ph.D. degree.

Dissertation

The doctoral dissertation is an essential part of this program. A topic will be selected by the student, under the advice and guidance of a major professor (thesis adviser) and a dissertation committee chaired by the major professor. Students are encouraged to begin some research activity as early as possible during the second year of their graduate studies. The dissertation must contain an original contribution of publishable quality to the knowledge of statistics that may expand the theory or methodology of statistics, or expand or modify statistical methods to solve a critical problem in applied disciplines. Acceptance of the dissertation by three designated members of the dissertation committee follows Graduate Studies guidelines (Plan A with defense). The dissertation must be completed and submitted to the dissertation committee prior to taking the final examination.

Final Examination

Defense of the dissertation before the five-member dissertation committee (three faculty who read the committee, plus two for the exam only) will constitute the final examination for the Ph.D. degree. The final examination must be passed within four years after promotion to Candidacy, unless a special exception is granted. Pass or no pass is determined by a vote of the dissertation committee. Title and abstract of the Ph.D. Defense presentation will be distributed to all faculty and students of the Graduate Program in Statistics, who are invited to attend the presentation portion of the examination. The subsequent question period is a closed session between the student and the committee.

Title and abstract of the Ph.D. Defense presentation will be distributed to all faculty and students of the Graduate Program in Statistics, who are invited to attend the presentation.

Normative Time to Degree

The Normative time to Degree is four to five years.

Sample Study-Plan

Every full-time student at UC Davis is required to take 12 units of coursework per quarter. Financial support, if granted, is contingent on normal progress towards the degree goal. In addition to the coursework as outlined below, students will take Statistics 290 and generally will take additional electives later on, in consultation with their major professor.
The following would be a typical program for a well-prepared student seeking a Ph.D. degree who opts for the fast track.

Year 1

Fall
Winter
Spring
Statistics 231A
Statistics 231B
Statistics 231C
Statistics 232A
Statistics 232B
Statistics 232C
Statistics 390
Statistics 242/243
Statistics 401
Ph.D. Pre-Qualifying Written Exam

Year 2

Fall
Winter
Spring
Statistics Elective
Statistics Elective
Research
Statistics Elective
Statistics Elective
Statistics Elective
Ph.D. Qualifying Exam
Statistics 401

Year 3, 4

Complete requirements for the Ph.D. degree, including Dissertation and Defense

For the pdf of our official requirements, please refer to the Statistics graduate student handbook.
Degree Requirements approved by Graduate Council May 17, 2010.
DateSpeakerInstitutionTitle / Abstract
Thursday Sep 22
Victor SoloUniv of New South Wales,  Australia“System Identification for Multivariate Point Processes with Applications to Neural Coding, High Frequency Finance and Genomics” - ABSTRACT
ThursdayOct 6Axel MunkGeorg August Universität Göttingen, Germany"Nanostatistics – Statistics for Nanoscopy"ABSTRACT
Friday, Oct 7 (11am)Axel MunkGeorg August Universität Göttingen, Germany"Multiscale Blind Source Separation"ABSTRACT
ThursdayOct 13Rajarshi GuhaniyogiUC Santa Cruz"Scalable Bayesian regression framework for tensor valued objects" - ABSTRACT
Friday Oct 14Debasis SenguptaIndian Statistical Institute, Kolkata / UC Santa Barbara"Feature sensitive and automated curve registration with paleo-climatic application" - ABSTRACT
ThursdayOct 20Hira KoulMichigan State Univ."A Goodness-of-fit test for marginal distribution of linear random fields with long memory" - ABSTRACT
Friday Oct 21Daniel McDonaldIndiana Univ. Bloomington"Approximation-regularization for the analysis of large data sets" - ABSTRACT
Thursday Oct 27Luis RademacherDept. Math, UC Davis"Provably efficient high dimensional feature extraction" - ABSTRACT
Thursday Nov 3Mladen KolarUniversity of Chicago, Booth School of Business“Inference in high-dimensional semi-parametric graphical models” - ABSTRACT
Thursday Nov 10Jennifer SinnottOhio State Univ."Kernel Machine Regression Methods in Risk Prediction" - ABSTRACT
Tuesday Nov 15Shahin TavakoliUniv. of Cambridge, UK"Spatial modeling of Object Data: Analysing dialectal sound changes across the UK" - ABSTRACT
Wednesday Nov 16*MSB 2112
Sanjay ChaudhuriNational Univ. Singapore"Hamiltonian Monte Carlo In Bayesian Empirical Likelihood Computation" - ABSTRACT
Thursday Nov 17Shuheng ZhouUniv. Michigan"Computational and statistical convergence for graph estimation: Just Relax" - ABSTRACT
Thursday Dec 1Johannes LedererUniv. Washington“Efficient Feature Selection With Big Data” - Abstract to come
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