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  Graduate School-New Brunswick 2005-2007 Programs, Faculty, and Courses Statistics and Biostatistics 960 Programs  

Programs

The faculty of statistics and biostatistics offers graduateprograms leading to the master of science and doctor of philosophydegrees. The M.S. program emphasizes statistical methods andapplications and provides options in biostatistics, quality managementand productivity, and data mining. The Ph.D. program offersspecializations in applied and theoretical statistics and probabilitytheory. The master of philosophy is available to doctoral candidates.

M.S. candidates must complete 30 course credits, pass a comprehensiveexamination, and submit an approved essay. The required courses for theM.S. degree include 16:960:563 Regression Analysis; 16:960: 582Introduction to Methods and Theory of Probability; 16:960:583 Methodsof Inference; 16:960:586 Interpretation of Data I; and 16:960:590Design of Experiments. Requirements for the M.S. program may besatisfied in a part-time evening program.

Students maycomplete the M.S. program with or without one of the following threeoptions. The option in biostatistics requires 16: 960:584, 585Biostatistics I, II; and either 16:960:542 Life Data Analysis or16:960:553 Categorical Data Analysis, in addition to the generalrequirements of the M.S. program. The option in quality management andproductivity, offered in cooperation with the graduate program inindustrial and systems engineering, requires 16:960:540 StatisticalQuality Control I; 16:960:542 Life Data Analysis; 16:960:591 AdvancedDesign of Experiments; 16:540:580 Quality Management; and 16:540:585Systems Reliability Engineering, in addition to the generalrequirements of the M.S. program. The option in data mining, offered incooperation with the graduate program in computer science, requires16:960:567 Applied Multivariate Analysis; 16:960:587 Interpretation ofData II; 16:960:588 Data Mining; 16:198:513 Design and Analysis of DataStructures and Algorithms; and 16:198:536 Machine Learning, and waivesthe requirement of 16:960:590.

The Ph.D. program requires 48course credits and a dissertation. Research work follows successfulcompletion of qualifying examinations. The first of these examinationsis taken near the end of the first year of study after completion of16:960:592 Theory of Probability; 16:960:593 Theory of Statistics; and16:960:680 Advanced Probability Theory I. The second examination isgenerally taken in the second or third year of study after completionof 16:960:652, 653 Advanced Theory of Statistics I, II; 16:960:663Regression Theory; and 16:960:681 Advanced Probability Theory II. Inaddition to these seven core courses for the qualifying examinations,the Ph.D. program requires 16:960:587 Interpretation of Data II; twomore 3-credit courses in statistics at the 600 level; 24 researchcredits; and three terms of 16:960:693 Current Topics in Statistics.

All Ph.D. candidates are required to demonstrate proficiency in oneforeign language related to their chosen fields or in computerprogramming relevant to statistics. While there is no formal residencyrequirement, the faculty urges Ph.D. candidates to spend at least onefull academic year in residence.

An entering Ph.D. studentshould have a good background in mathematics, including advancedcalculus and linear algebra. These latter subjects, however, are notrequired to gain admission. Each student selects his or her program inconference with a department adviser. There is a wide range of courseofferings and areas of research. These include statistical inference,estimation theory, operations research, hypothesis testing, decisiontheory, biostatistics, empirical Bayes and Bayes methods, regressionanalysis, analysis of variance, experimental design, multivariateanalysis, nonparametric statistics, data mining, image and signalprocessing, statistical computing, sampling theory, robust statistics,survival analysis and incomplete data, longitudinal data, sequentialanalysis, quality-control theory, time-series analysis, appliedprobability, stochastic processes, and probability theory, includingstopping rules and martingales. Information about recommended coursesequences for degrees is available upon request from the office of thegraduate 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.


 
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