The faculty of statistics 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 management and 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 and productivity, 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 examinations is taken near
the end of the first year of study after completion of 16:960:592
Theory of Probability; 16:960:593 Theory of Statistics; and 16:960:680
Advanced Probability Theory I. The second examination is generally
taken in the second or third year of study after completion of
16:960:652, 653 Advanced Theory of Statistics I, II; 16:960:663
Regression Theory; and 16:960:681 Advanced Probability Theory 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; 24 research
credits; and three terms of 16:960:693 Current Topics in Statistics.
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.
Further information may be found on the web at http://www.stat.rutgers.edu/curriculum/gradcurr.html.
