The faculty of statistics and biostatistics offers
graduate programs leading to the master of science and doctor of philosophy degrees. The
M.S. program emphasizes statistical methods and applications and
provides options in biostatistics, quality productivity,
and data mining. The Ph.D. program offers specializations in applied
and theoretical statistics and probability theory. The master of
philosophy is available to doctoral candidates.
M.S. candidates
must complete 30 course credits, pass a comprehensive examination, and
submit an approved essay. The required courses for the M.S. degree
include 16:960:563 Regression Analysis; 16:960:582 Introduction to
Methods and Theory of Probability; 16:960:583 Methods of Inference;
16:960:586 Interpretation of Data I; and 16:960:590 Design of
Experiments. Requirements for the M.S. program may be satisfied in a
part-time evening program.
Students may complete the M.S.
program with or without one of the following three options. The option
in biostatistics requires 16:960:584,585 Biostatistics I,II; and
either 16:960:542 Life Data Analysis or 16:960:553 Categorical Data
Analysis, in addition to the general requirements of the M.S. program.
The option in quality management, offered in
cooperation with the graduate program in industrial and systems
engineering, requires 16:960:540 Statistical Quality Control I;
16:960:542 Life Data Analysis; 16:960:591 Advanced Design of
Experiments; 16:540:580 Quality Management; and 16:540:585 Systems
Reliability Engineering, in addition to the general requirements of the
M.S. program. The option in data mining, offered in cooperation with the
graduate program in computer science, requires 16:960:567 Applied
Multivariate Analysis; 16:960:587 Interpretation of Data II; 16:960:588
Data Mining; 16:198:513 Design and Analysis of Data Structures and
Algorithms; and 16:198:536 Machine Learning, and waives the requirement
of 16:960:590.
The Ph.D. program requires 48 course credits and
a dissertation. Research work follows successful completion of qualifying examinations. The first of these taken near
the end of the first year of study after completion of 16:960:592 Theory
of Probability and 16:960:593 Theory of Statistics. The second examination is generally taken in the
second or third year of study after 16:960:652,653
Advanced Theory of Statistics I,II; 16:960:663 Regression Theory; and
16:960:680-681 Advanced Probability Theory I and II. In addition to these seven
core courses for the qualifying examinations, the Ph.D. program requires
16:960:587 Interpretation of Data II; two more 3-credit courses in
statistics at the 600 level; and three semesters of
16:960:693 Current Topics in Statistics. The courses
16:960:680-681 may be replaced in the curriculum and on the oral exam by two 600-level courses chosen with approval of the graduate director.
All Ph.D. candidates
are required to demonstrate proficiency in one foreign language related
to their chosen fields or in computer programming relevant to
statistics. While there is no formal residency requirement, the faculty
urges Ph.D. candidates to spend at least one full academic year in
residence.
An entering Ph.D. student should have a good
background in mathematics, including advanced calculus and linear
algebra. These latter subjects, however, are not required to gain
admission. Each student selects his or her program in conference with a
department adviser. There is a wide range of course offerings and areas
of research. These include statistical inference, estimation theory,
operations research, hypothesis testing, decision theory, biostatistics,
empirical Bayes and Bayes methods, regression analysis, analysis of
variance, experimental design, multivariate analysis, nonparametric
statistics, data mining, image and signal processing, statistical
computing, sampling theory, robust statistics, survival analysis and
incomplete data, longitudinal data, sequential analysis, quality-control
theory, time-series analysis, applied probability, stochastic processes,
and probability theory, including stopping rules and martingales.
Information about recommended course sequences for degrees is available
upon request from the office of the graduate director. See also operations research in this chapter.
The graduate program in statistics and biostatistics collaborates with the M.S. program in mathematical finance.
Further information may be found on the web at http://www.stat.rutgers.edu/curriculum/gradcurr.html.
