PhD Program Description
The degree of Doctor of Philosophy is a research degree, conferred in recognition of marked ability and scholarship and high scholastic attainment and original research in Statistics. The degree is conferred after successful completion of an acceptable thesis summarizing substantial results of original research work relevant to Statistics. Thesis work will be carried on with the general guidance and under the supervision of the candidate's Thesis Advisor.
Areas of specialization for research include any topic suitable for research in applied or theoretical statistics, including statistical inference, estimation theory, hypothesis testing, machine learning, decision theory, empirical Bayes and Bayes methods, regression analysis, analysis of variance, statistical computing, experimental design, multivariate analysis, nonparametric statistics, sequential analysis, time series analysis, applied probability, stochastic processes, and probability theory.
Formal Credit Requirements
Ph.D. candidates must ordinarily have at least 72 semester-hours of approved graduate credits. This will generally consist of 48 hours of course credits and the remainder of the 24 hours as research credits.
Transfer of Credits
Up to 12 credits of such acceptable credits may be permitted to be applied for the Ph.D. degree. This is subject to individual consideration.
A Guide for Courses and Electives for Ph.D. in Applied and Mathematical Statistics
Required Courses: (To be taken in the first year of study)
592 Theory of Probability (Fall)
593 Theory of Statistics (Fall)
594 Advanced Modern Statistical Inference II (Spring)
596 Advanced Applied Statistics I (Fall)
597 Advanced Applied Statistics II (Spring)
654 Stochastic Processes (Spring)
Electives:
652 Advanced Theory of Stat I (Fall)
653 Advanced Theory of Stat II (Spring)
663 Regression Theory (Fall)
665 Advanced Time Series Analysis (Fall)
667 Multivariate Analysis (Spring)
669 Advanced Spatial Statistics (Spring)
687-688 Seminar in Applied and Mathematical Statistics (Spring)
690 Special Topics (topics on rotating basis): Ethical Statistical Learning, Reinforcement Learning and Generative Models, History of Probability & Statistics
691 Special Topics (topics on rotating basis): Applied Statistics Seminar
Graduate courses offered in our MS Program, subject to approval of advisor and/or graduate directors can be foundhere.
Approved graduate courses offered by other departments (e.g. Math, CS, or ECE) can be foundhere.
Link to Typical Ph.D. Plan
Examination Requirement
A precondition to being formally admitted as a Ph.D. candidate is that the student pass the Ph.D. Examinations, the purpose of which is to determine the breadth of the student's mastery of their major and minor fields. The first of these exams is a comprehensive written qualifying exam on all first-year course material. The qualifying exam is taken before the second-year and consists of three parts: one exam each on mathematical statistics, probability theory, and applied statistics. Progress toward the Ph.D. is monitored throughout the second and third years, culminating in a written thesis proposal (due by the end of the 2nd semester of the third year) and an oral thesis proposal (presented no later than the 1st semester of the fourth year).
Past Ph.D. Exams & Solutions
Past exams and solutions can be found here:
https://rutgersconnect.sharepoint.com/sites/stat-ms_phd_past_examsGo to documents.
