Computer Science (M.S.) - Graduate - 2012 University Catalog
You are viewing the 2012 University Catalog. Please see the newest version of the University Catalog for the most current version of this program's requirements.
The graduate program in computer science is designed for students interested in pursuing computer science theoretically as well as practically at an advanced level. While introducing students to newly developing areas of computer science, this program emphasizes the foundations and concepts of the field. Concepts are developed rather than routine programming skills. Students are prepared for professional work in the design and implementation of software systems, data base systems, operating systems, artificial intelligence, expert systems, graphics, simulation and algorithms for discrete and continuous structures that will aid in the solution of problems encountered in the scientific and business sector. The curriculum is designed to allow students to develop skills needed to achieve leadership positions in business, industry, and government in computer science or in related fields that are computer science intensive. The program also prepares teachers of computer science at the two year college, high school and middle school levels.
The graduate program in computer science began in 1978. At present, there are 12 full-time faculty in the Department of Computer Science. the special interests of the faculty include algorithms, artificial intelligence, automata theory, automated theorem proving, bioengineering, compilers, computer science education, complexity theory, computational linguistics, computational logic, cryptography, databases, data mining and knowledge discovery, design and management of information systems, expert systems, fault-tolerant computing, graphics, machine organization and architecture, neural networks, non-linear phenomena and fuzzy logic, operating systems, parallel and distributed computing, program verification, pixel and image processing, robotics, software engineering, scientific computing, and telecommunications. The department has the advantage of having professional computer scientists as both faculty and visiting specialists. The visiting specialists are drawn from the aerospace, chemical, computer, and pharmaceutical industries. This mix of faculty affords students the opportunity to obtain an education in both the practical and theoretical aspects of computer science.
Computer facilities within the College of Science and Mathematics currently comprise a local area network (SCINet) of Sun servers and workstations, as well as Dell and Macintosh teaching laboratories. The Sun network comprises four Enterprise servers, a student laboratory with twenty Ultra 10 workstations, and workstations in faculty offices. The computers of this network run under UNIX operating system. Available software packages include: Maple, MATLAB, Iris Explorer, LaTEX, Rational Rose, SAS, Splus, Ingres, MySQL, JavaStudio, and JavaWorkshop. Programming language include: C, C++, Java, Ada, FORTRAN, Pascal, LISP, Prolog, Perl and Smalltalk. In addition, Montclair State University maintains a DEC Alpha 2100 (running the VMS operating system), on which any MSU student may establish an account. Software available on this machine include: Ada, C, C++, COBOL, FORTRAN, GPSS, Ingres, LISP, Macro, Maple, Minitab, Pascal, PL/1, Prolog, SAS, SAS graphics, SPSSX and SPSS graphics. The University also maintains a number of microcomputer labs throughout the campus. Access to the Alpha and CSAM Sun network is available from most of these microcomputers via a campus-wide local area network (MSUNet). In addition, these microcomputers support a wide variety of software such as JMP, Mac Spin, Data Desk, Solo, Statistix, and Office for student use. Montclair State University recently became its own Internet Service Provider (MSU-ISP). All students and faculty may establish Internet Accounts. These, as well as dial-up lines, provide remote access to computers on campus.
Students desiring to enter the MS in Computer Science without an appropriate background in computer science can obtain the necessary foundation in computer science and mathematics by taking courses in our prerequisite program. Upon satisfactory completion of part or all of the program, students are admitted to the Master of Science program.
COMPUTER SCIENCE
Complete 33 semester hours including the following 4 requirement(s):
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REQUIRED COURSES
Complete 4 courses for 12 semester hours:
CMPT 580 Machine Organization and Architecture (3 hours lecture) 3 CMPT 581 Systems Software Design (3 hours lecture) 3 CMPT 583 Computer Algorithms (3 hours lecture) 3 CMPT 594 Software Engineering and Reliability (3 hours lecture) 3 -
REQUIRED TWO-COURSE SEQUENCE
Complete 1 of the following options for 6 semester hours:
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DATABASE SPECIALIZATION
Complete
CMPT 586 File Structures and Databases (3 hours lecture) 3 CMPT 592 Data Base Design and Implementation (3 hours lecture) 3 -
NETWORKING SPECIALIZATION
Complete
CMPT 596 Principles of Data Communication (3 hours lecture) 3 CMPT 696 Local Area Networks (3 hours lecture) 3 -
SYSTEM SOFTWARE SPECIALIZATION
Complete
CMPT 584 Operating System Design (3 hours lecture) 3 CMPT 591 Compiler Theory and Construction (3 hours lecture) 3
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ADDITIONAL REQUIRED COURSE
Complete 1 course for 3 semester hours from the following list
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CULMINATING EXPERIENCE & ELECTIVES
Complete the following 2 requirements for a total of 12 semester hours:
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ELECTIVES
Complete 12 semester hours (or 9 semester hours if completing CMPT 697 or CMPT 698) from:
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CULMINATING EXPERIENCE
Complete 1 of the following options:
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THESIS
Students must have a 3.3 or higher in the required core courses to register for the Thesis:
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Complete for 3 semester hours. Submit completed Thesis Original and one copy to the Graduate Office. See Thesis Guidelines.
CMPT 698 Master's Thesis 3
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MASTERS PROJECT
Complete for 3 semester hours.
CMPT 697 Master's Project in Computer Science (3 hours lecture) 3 -
COMPREHENSIVE EXAM
Successfully complete the Comprehensive Exam.
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Course Descriptions:
CMPT574: Pixel and Image Processing (3 hours lecture)
This course provides an introductory and comprehensive treatment of pixel and image processing with applications to fine arts, face recognition, etc. Topics include sampling and quantization, convolution, equalization, filtering, image segmentation, image operations, morphological image processing. 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT575: Introduction to Computer Graphics (3 hours lecture)
An introduction to computer graphics, including the algorithms to generate two-dimensional and three-dimensional graphical pictures. An overview of ray tracing, shading and color theory. Interactive graphics. Graphics devices. 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT576: Object-Oriented Software Development (3 hours lecture)
Introduction to the major features of the object-oriented paradigm and their realization in an object-oriented programming language. Introduction to major methods and tools used in object-oriented analysis and design. Implementation and testing issues. 3 sh.
Prerequisites: CMPT 581, CMPT 583 and permission of graduate coordinator.
CMPT578: Introduction to Artificial Intelligence (3 hours lecture)
An introduction to artificial intelligence including representations of knowledge, problem solving, games, heuristics and backtracking, expert systems, theorem proving, the language LISP and PROLOG. 3 sh.
Prerequisites: CMPT 583 and permission of graduate coordinator.
CMPT580: Machine Organization and Architecture (3 hours lecture)
Basic computer organization and design, digital functions, data representation, microprogramming, CPU organization, the assembler language, and addressing techniques. Required of majors. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT581: Systems Software Design (3 hours lecture)
Assemblers, macroprocessors, linkers and loaders, introduction to compilers and run facilities. Required of majors. 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT582: Theory of Automata and Formal Languages (3 hours lecture)
Languages and grammars, finite automata and regular grammars, context free grammars, push-down automata, Turing machines, computability, deterministic languages, linear bounded automata and stack automata. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT583: Computer Algorithms (3 hours lecture)
Algorithms: definition, design and analysis; sorting and searching techniques and introductory dynamic programming studied as algorithms with complexity theory and optimization techniques applied. Required of majors. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT584: Operating System Design (3 hours lecture)
Design and implementation of operating systems, multiprogramming, multiprocessor, device management, scheduling, virtual memory, case studies. 3 sh.
Prerequisites: CMPT 581, and permission of graduate coordinator.
CMPT585: Topics in Computer Science (3 hours lecture)
Recent developments in the field. Topics such as Monte Carlo methods, graphics, expert systems, security, networks and special areas of applications. May be repeated twice for a maximum of 9.0 credits as long as the topic is different. 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT586: File Structures and Databases (3 hours lecture)
Secondary storage devises. Data transfer. Primary and secondary access methods. Sequential and random access methods. File design. File organizations and corresponding processing. File maintenance. Sorting large files. Databases concepts. Required of majors. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT587: Microcomputers and Computer Interfaces (3 hours lecture)
Introduction to geneology, manufacture and hardware design of microprocessors, microcomputer architecture, instruction sets and programming, microcomputer peripherals and interfaces. 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT588: Fundamentals of Programming Languages (3 hours lecture)
A comparative approach to modern programming languages with emphasis on non-imperative languages, and an introduction to parallel languages. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT589: Computer Simulation of Discrete Systems (3 hours lecture)
Introduction to simulation and discrete simulation models. Queuing theory and stochastic processes. Simulation methodology including generation of random numbers and variates, design of simulation experiments, analysis of data generated by simulation experiments and validation of models. Survey of current simulation languages and selected applications. 3 sh.
Prerequisites: CMPT 580, permission of graduate coordinator.
CMPT590: Computer Simulation of Continuous Systems (3 hours lecture)
Computer simulation of continuous systems with emphasis on conservation principles and governing equations, numerical treatment of systems of algebraic and differential equations, the use of software packages and simulation languages, verification and validation techniques, and interpretation and presentation of results. 3 sh.
Prerequisites: CMPT 580, permission of graduate coordinator.
CMPT591: Compiler Theory and Construction (3 hours lecture)
Introduction to the formal description of programming languages, the theory of parsing, and the concepts and techniques used in the construction of compilers. 3 sh.
Prerequisites: CMPT 581, permission of graduate coordinator.
CMPT592: Data Base Design and Implementation (3 hours lecture)
To develop in-depth understanding of data base concepts and issues. The major emphasis of the course is on the conceptual (logical) organization, retrieval, and manipulation of data. Required of majors. 3 sh.
Prerequisites: CMPT 586, permission of graduate coordinator.
CMPT593: Structured System Design and Analysis (3 hours lecture)
A study of the design of large scale computer systems relative to the constraints imposed by hardware, software and particular types of applications. Recent work in automated system design will be discussed. 3 sh.
Prerequisites: CMPT 586, and permission of graduate coordinator.
CMPT594: Software Engineering and Reliability (3 hours lecture)
Principles and methods for the analysis, design, implementation, testing, and verification of software systems. Topics include requirements analysis, domain analysis, implementation, testing, verification, and software management. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT596: Principles of Data Communication (3 hours lecture)
Physical and logical aspects of data communications: analog-digital, broadband-baseband, TDM-FDM, protocols, modulation techniques, hardware for communication. 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT678: Neurocomputing (3 hours lecture)
Basic neural network concepts, definitions, and building blocks; learning laws; simple implementations; associative networks; mapping networks; survey of applications. 3 sh.
Prerequisites: CMPT 583, and permission of graduate coordinator.
CMPT680: Parallel Architectures and Algorithms (3 hours lecture)
This course provides a study of the state-of-art of parallel processing algorithms and architectures. Parallel processing uses multiple processors working together in a synchronized fashion to solve large problems fast. 3 sh.
Prerequisites: CMPT 580 and CMPT 583, and permission of graduate coordinator.
CMPT683: Advanced Computer Algorithms (3 hours lecture)
Dynamic programming, game trees and backtracking techniques, branch and bound, polynomial evaluation and fast Fourier transform algorithms; complexity and analysis, and optimization techniques will be applied. NP-hard problems and NP-completeness. 3 sh.
Prerequisites: CMPT 583, and permission of graduate coordinator.
CMPT690: Independent Study in Computer Science
Independent study under the direction of a faculty member, offering the opportunity to pursue topics in computer science which may be outside the scope of regular curricular offerings or may be an extension of an existing course or courses. Approval must be obtained from the graduate coordinator or and faculty advisor. May be repeated once for a maximum of 6.0 credits. 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT694: Software Quality Assurance (3 hours lecture)
This course examines (i) planned and systematic patterns of all actions necessary to provide adequate confidence that a product conforms to established requirements, and (ii) a set of activities designed to evaluate the process by which high-quality complex software products are developed. 3 sh.
Prerequisites: CMPT 594 or permission of graduate advisor.
CMPT695: Seminars in Computer Science (1-4 hours seminar)
Guided study of selected topics in major field of interest. 1 - 4 sh.
Prerequisites: CMPT 581, 583, and 586 and permission of graduate coordinator.
CMPT696: Local Area Networks (3 hours lecture)
Fundamental issues and concepts underlying Local Area Network (LAN) development via microcomputers: topology, transmission media and technology, error control, protocols. 3 sh.
Prerequisites: CMPT 596, and permission of graduate coordinator.
CMPT697: Master's Project in Computer Science (3 hours lecture)
Analysis of a significant problem related to computing and design of a solution. Where appropriate, implementation and testing as well as documentation of the solution. 3 sh.
Prerequisites: Completion of the computer science required core courses and permission of graduate coordinator.
CMPT698: Master's Thesis
Independent research project done under faculty advisement. Students must follow the MSU Thesis Guidelines, which may be obtained from the Graduate School. Students should take CMPT 699 if they don't complete CMPT 698 within the semester. 3 sh.
Prerequisites: Departmental approval.
MATH520: Set Theory (3 hours lecture)
Historical development, paradoxes, ordered sets, Schroder-Bernstein theorem, axiom of choice, transfinite induction, cardinal and ordinal numbers. 3 sh.
Prerequisites: MATH 222 and permission of graduate program coordinator.
MATH521: Real Variables I (3 hours lecture)
Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. 3 sh.
Prerequisites: MATH 426 and permission of graduate program coordinator.
MATH522: Real Variables II (3 hours lecture)
Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. 3 sh.
Prerequisites: MATH 521, permission of graduate program coordinator.
MATH525: Complex Variables I (3 hours lecture)
Integration and differentiation in the complex domain, Cauchy's theorem, Cauchy's integral formula, Laurent expansion, residues, elements of conformal mapping, series and product representations. 3 sh.
Prerequisites: MATH 426 and permission of graduate program coordinator.
MATH526: Complex Variables II (3 hours lecture)
Integration and differentiation in the complex domain, Cauchy's theorem, Cauchy's integral formula, Laurent expansion, residues, elements of conformal mapping, series and product representations. 3 sh.
Prerequisites: MATH 525, permission of graduate program coordinator.
MATH530: Mathematical Computing (3 hours lecture)
Introduction to mathematical computing techniques using a computer algebra system and algorithmic approach to solving mathematical problems. Mathematical applications taken from various areas of mathematics, the sciences, engineering, and business. 3 sh.
Prerequisites: Permission of the graduate program coordinator or consent of the instructor.
MATH531: Abstract Algebra I (3 hours lecture)
Basic algebraic structures including groups, rings, fields, modules and lattices. 3 sh.
Prerequisites: MATH 431 and permission of graduate program coordinator.
MATH532: Abstract Algebra II (3 hours lecture)
Basic algebraic structures including groups, rings, fields, modules and lattices. 3 sh.
Prerequisites: MATH 531, permission of graduate program coordinator.
MATH535: Linear Algebra I (3 hours lecture)
Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. 3 sh.
Prerequisites: MATH 335 and permission of graduate program coordinator.
MATH536: Linear Algebra II (3 hours lecture)
Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. 3 sh.
Prerequisites: MATH 535, permission of graduate program coordinator.
MATH537: Mathematical Logic (3 hours lecture)
Propositional and predicate calculus, model theory, Godel's completeness theorems and decidability. 3 sh.
Prerequisites: MATH 425 and permission of graduate program coordinator.
MATH540: Probability (3 hours lecture)
Sample spaces and events, combinatorial analysis, conditional probability and stochastic independence, random variables and probability distributions, expected value and variance, probability generating functions, continuous random variables. 3 sh.
Prerequisites: MATH 340 and permission of graduate program coordinator.
MATH551: Topology (3 hours lecture)
Basic point-set topology, topological spaces, homeomorphisms, compactness, connectedness, separation properties, uniformities, metrizability, introductory algebraic topology, homology groups and homotopy. 3 sh.
Prerequisites: MATH 425, and permission of graduate program coordinator.
MATH554: Projective Geometry (3 hours lecture)
Projective planes and spaces are studied by synthetic and analytic approaches. Topics covered include the theorems of Desargues and Pappus, harmonic sequences, projectivities, coordinatization, finite planes, and conics. 3 sh.
Prerequisites: MATH 335 and permission of graduate program coordinator.
MATH555: Differential Geometry (3 hours lecture)
Application of vectors to the study of classical three-dimensional geometry. Topics include: plane and space curves, first and second fundamental forms, lines of curvature, asymptotic lines, geodesics. 3 sh.
Prerequisites: MATH 222 and permission of graduate program coordinator.
MATH560: Numerical Analysis (3 hours lecture)
Error analysis, interpolation and approximation theory, numerical solution of linear and nonlinear equations, numerical differentiation and integration, numerical solution of differential equations. 3 sh.
Prerequisites: MATH 335, and permission of graduate program coordinator.
MATH564: Ordinary Differential Equation (3 hours lecture)
Linear and nonlinear equations, Green's functions, power series solutions, autonomous systems, existence and uniqueness, singularities, Sturm-Liouville systems. 3 sh.
Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.
MATH566: Partial Differential Equations (3 hours lecture)
First order equations, separation of variables, series solutions, hyperbolic, parabolic and elliptic equations, characteristics, transform methods. 3 sh.
Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.
MATH568: Applied Mathematics: Continuous (3 hours lecture)
Formulation, manipulation and evaluation of mathematical models of continuous systems. Topics selected from: conservation principles and the classical equations of mathematical physics, applications of the qualitative and quantitative theory of ordinary and partial differential equations, optimization, calculus of variations, stability theory, stochastic models. 3 sh.
Prerequisites: MATH 335, and 340, and 420, and 425, and permission of graduate program coordinator.
MATH569: Applied Mathematics: Discrete (3 hours lecture)
Introduction to the basic ideas of discrete mathematics and its applications. Counting principles, permutations, combinations, algorithms, complexity, graphs, trees, searching and sorting, recurrence relations, generating functions, inclusion-exclusion, the pigeonhole principle, chromatic number, eulerian chains and paths, hamiltonian chains and paths, flows in networks, finite Markov chains. 3 sh.
Prerequisites: MATH 335, and 340, and 425, and permission of graduate program coordinator.
MATH580: Combinatorial Mathematics (3 hours lecture)
Arrangements and selections, binomial coefficients, Stirling numbers, generating functions, recurrence relations, inclusion-exclusion, Polya enumeration formula, combinatorial graph theory, combinatorial geometries. 3 sh.
Prerequisites: MATH 222 and graduate program coordinator's permission.
MATH581: Graph Theory (3 hours lecture)
Graphs, digraphs, and trees. Connectivity, separability, planarity, and colorability. Cliques, independent sets, matchings, flows and tours. Graphs as mathematical models; graph algorithms. 3 sh.
Prerequisites: MATH 222, and 335, and graduate program coordinator's permission.
MATH584: Operations Research (3 hours lecture)
An in-depth study of one or at most two topics in operations research, selected from linear programming and game theory, linear and nonlinear programming, queuing theory, inventory theory, simulation models. 3 sh.
Prerequisites: MATH 425 and STAT 440 and permission of graduate program coordinator.
MATH590: Advanced Topics (3 hours lecture)
An in-depth study of a topic or topics selected from areas such as algebra, analysis, geometry, probability and statistics, and applied mathematics, with special emphasis upon recent developments in the field. May be repeated once for a maximum of 6.0 credits as long as the topic is different. 3 sh.
Prerequisites: Graduate program coordinator's permission.
MATH591: Applied Industrial Mathematics (3 hours lecture)
Formulation, modeling, and solution of mathematical problems from engineering, science and business. Topics include statistical distributions, Monte Carlo method, function fitting, transforms optimization, regression analysis, cost-benefit analysis, ordinary differential equations, partial differential equations, numerical methods, divided differences, splines, Galerkin's method, and finite elements. 3 sh.
Prerequisites: MATH 335, MATH 425, MATH 530, STAT 440 or permission of graduate program coordinator.
MATH595: Seminar (1-4 hours seminar)
Guided study of selected topics in major field of interest. May be repeated once for a maximum of 6.0 credits as long as the topic is different. 1 - 4 sh.
Prerequisites: Graduate program coordinator's permission.
MATH690: Independent Study in Mathematics
Independent study under the direction of a faculty member, offering the opportunity to pursue topics in mathematics which may be outside the scope of regular curricular offerings or may be an extension of an existing course or courses. Approval must be obtained from the graduate coordinator and faculty advisor. May be repeated once for a maximum of 6.0 credits during the graduate program. 3 sh.
Prerequisites: Permission of graduate program coordinator. Departmental approval.
STAT541: Applied Statistics (3 hours lecture)
Review of estimation and hypothesis testing for one sample and two sample problems; introduction to non-parametric statistics and linear regression; fundamental principles of design, completely randomized design, randomized block design, latin square, and 2 factor design. 3 sh.
Prerequisites: STAT 330 or STAT 443 and permission of graduate program coordinator.
STAT542: Statistical Theory I (3 hours lecture)
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chi-squared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, Neyman-Pearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.
Prerequisites: STAT 541 and permission of graduate program coordinator.
STAT543: Statistical Theory II (3 hours lecture)
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chi-squared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, Neyman-Pearson Lemma, likelihood ratio tests. The impact of the above theory on areas such as regression analysis, analysis of variance and analysis of discrete data. 3 sh.
Prerequisites: STAT 542 and permission of graduate program coordinator.
STAT544: Statistical Computing (3 hours lecture)
Computer systems for data analysis and data graphics, and intermediate level statistical methodology are investigated. Several statistical computing packages are utilized and evaluated. 3 sh.
Prerequisites: STAT 541 or STAT 548, and CMPT 183, and permission of graduate program coordinator.
STAT545: Practicum in Statistics I
An applied experience in which students work with practitioners in industry, government or research organizations utilizing statistical techniques in a research setting. Students will work with statisticians on projects involving experimental design and data collection as well as the analysis and interpretation of the data. May be repeated once. 3 sh.
Prerequisites: STAT 541, STAT 544, and STAT 547 or STAT 548, and permission of graduate program coordinator.
STAT546: Non-Parametric Statistics (3 hours lecture)
Selected distribution-free tests and estimation techniques including sign, Kolmogorov-Smirnov, Wilcoxon signed rank, Mann-Whitney, Chi-square, rank correlation, Kendall's Tau, Kruskal-Wallace, Friedman, McNemar, and others. 3 sh.
Prerequisites: STAT 330 and permission of graduate program coordinator.
STAT547: Design and Analysis of Experiments (3 hours lecture)
Fundamental principles of design; fixed, random and mixed models; factorial designs; designs with restricted randomization; split-plot design; confounding; fractional replication; experimental and sampling errors. 3 sh.
Prerequisites: STAT 541 or STAT 548, and permission of graduate program coordinator.
STAT548: Applied Regression Analysis (3 hours lecture)
Fitting equations to data; matrices, linear regression; correlation; analysis of residuals; multiple regression; polynomial regression; partial correlation; stepwise regression; regression and model building; regression applied to analysis of variance problems; introduction to nonlinear regression. 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT549: Sampling Techniques (3 hours lecture)
Sampling and survey methodology; basic sampling theory; simple, stratified, random, cluster, systematic and area sampling. Sampling errors and estimation procedures. 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT595: Topics in Statistics (3 hours lecture)
Topics such as exploratory data analysis, statistical graphics, statistical quality control and statistical quality assurance, Bayesian methods and Markov chain monte carlo studies. May be repeated twice for a total of 9.0 credits. 3 sh.
Prerequisites: Permission of graduate program coordinator.
STAT640: Biostatistics I (3 hours lecture)
Fundamental statistical concepts and methods used by statistical scientists in the health, biological, medical and pharmaceutical industries. Categorical data analysis, logistic regression, generalized linear models, nonparametric regression techniques. 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT641: Biostatistics II (3 hours lecture)
Fundamental statistical concepts and methods used by statistical scientists in the health, biological, medical and pharmaceutical industries. Survival analysis and designs for clinical trials. 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT642: Introduction to Stochastic Processes (3 hours lecture)
Generating functions, convolutions, recurrent events, random walk models, gambler's ruin problems, Markov chains and processes, time dependent stochastic processes, queuing theory and epidemic models. 3 sh.
Prerequisites: MATH 540 and permission of graduate program coordinator.
STAT645: Advanced Topics in Statistics (3 hours lecture)
Recent developments in statistical science. Topics such as data mining, statistical genomics, computationally intensive data-analytic methods, statistical consulting, dynamic statistical graphics and visualization, applied time series analysis. May be repeated with no limit as long as the topic is different. 3 sh.
Prerequisites: Permission of graduate program coordinator.
STAT646: Multivariate Analysis (3 hours lecture)
Analysis of multiple response variables simultaneously; covariance and the multivariate normal distribution; manova, discriminant functions; principle components and canonical correlations. 3 sh.
Prerequisites: STAT 541, STAT 548 and permission of graduate program coordinator.
STAT647: Practicum in Statistics II
An applied experience in which students work with practitioners in industry, government or research organizations utilizing advanced statistical techniques in a research setting. Students will be expected to exhibit the ability to work independently on projects involving advanced techniques in experimental design, analysis and interpretation of data. May be repeated once. 3 sh.
Prerequisites: STAT 542, STAT 545, at least one 600-level course, and permission of graduate program coordinator.
STAT648: Advanced Statistical Methods (3 hours lecture)
Advanced statistical concepts and methods used by statistical scientists in the analysis of designed experiments and observational studies. Response surface methodology, analysis of covariance, the general linear model, the cell means model and the analysis of variance of unbalanced or messy data. 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT649: Independent Study in Statistics
Independent study under the direction of a faculty member, offering the opportunity to pursue topics in statistics which may be outside the scope of regular curricular offerings or may be an extension of an existing course or courses. Approval must be obtained from the graduate coordinator and faculty advisor. May be repeated once for a maximum of 6.0 credits during the graduate program. 3 sh.
Prerequisites: Permission of graduate program coordinator and departmental approval.
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