Computer Science (M.S.)  Graduate  2011 University Catalog
You are viewing the 2011 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 fulltime 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, faulttolerant computing, graphics, machine organization and architecture, neural networks, nonlinear 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 campuswide 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 (MSUISP). All students and faculty may establish Internet Accounts. These, as well as dialup 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):

REQUIRED COURSES
Complete 4 courses for 12 semester hours:
CMPT 580 Machine Organization and Architecture 3 CMPT 581 Systems Software Design 3 CMPT 583 Computer Algorithms 3 CMPT 594 Software Engineering and Reliability 3 
REQUIRED TWOCOURSE SEQUENCE
Complete 1 of the following options for 6 semester hours:

DATABASE SPECIALIZATION
Complete
CMPT 586 File Structures and Databases 3 CMPT 592 Data Base Design and Implementation 3 
NETWORKING SPECIALIZATION
Complete
CMPT 596 Principles of Data Communication 3 CMPT 696 Local Area Networks 3 
SYSTEM SOFTWARE SPECIALIZATION
Complete
CMPT 584 Operating System Design 3 CMPT 591 Compiler Theory and Construction 3


ADDITIONAL REQUIRED COURSE
Complete 1 course for 3 semester hours from the following list

CULMINATING EXPERIENCE & ELECTIVES
Complete the following 2 requirements for a total of 12 semester hours:

ELECTIVES
Complete 12 semester hours (or 9 semester hours if completing CMPT 697 or CMPT 698) from:

CULMINATING EXPERIENCE
Complete 1 of the following options:

THESIS
Students must have a 3.3 or higher in the required core courses to register for the Thesis:

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


MASTERS PROJECT
Complete for 3 semester hours.
CMPT 697 Master's Project in Computer Science 3 
COMPREHENSIVE EXAM
Successfully complete the Comprehensive Exam.


Course Descriptions:
CMPT574: Pixel and Image Processing
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 hours lecture.) 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT575: Introduction to Computer Graphics
An introduction to computer graphics, including the algorithms to generate twodimensional and threedimensional graphical pictures. An overview of ray tracing, shading and color theory. Interactive graphics. Graphics devices. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT576: ObjectOriented Software Development
Introduction to the major features of the objectoriented paradigm and their realization in an objectoriented programming language. Introduction to major methods and tools used in objectoriented analysis and design. Implementation and testing issues. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 581, CMPT 583 and permission of graduate coordinator.
CMPT578: Introduction to Artificial Intelligence
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 hours lecture.) 3 sh.
Prerequisites: CMPT 583 and permission of graduate coordinator.
CMPT580: Machine Organization and Architecture
Basic computer organization and design, digital functions, data representation, microprogramming, CPU organization, the assembler language, and addressing techniques. Required of majors. (3 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT581: Systems Software Design
Assemblers, macroprocessors, linkers and loaders, introduction to compilers and run facilities. Required of majors. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT582: Theory of Automata and Formal Languages
Languages and grammars, finite automata and regular grammars, context free grammars, pushdown automata, Turing machines, computability, deterministic languages, linear bounded automata and stack automata. (3 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT583: Computer Algorithms
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 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT584: Operating System Design
Design and implementation of operating systems, multiprogramming, multiprocessor, device management, scheduling, virtual memory, case studies. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 581, and permission of graduate coordinator.
CMPT585: Topics in Computer Science
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 hours lecture.) 3 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT586: File Structures and Databases
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 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT587: Microcomputers and Computer Interfaces
Introduction to geneology, manufacture and hardware design of microprocessors, microcomputer architecture, instruction sets and programming, microcomputer peripherals and interfaces. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT588: Fundamentals of Programming Languages
A comparative approach to modern programming languages with emphasis on nonimperative languages, and an introduction to parallel languages. (3 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT589: Computer Simulation of Discrete Systems
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 hours lecture.) 3 sh.
Prerequisites: CMPT 580, permission of graduate coordinator.
CMPT590: Computer Simulation of Continuous Systems
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 hours lecture.) 3 sh.
Prerequisites: CMPT 580, permission of graduate coordinator.
CMPT591: Compiler Theory and Construction
Introduction to the formal description of programming languages, the theory of parsing, and the concepts and techniques used in the construction of compilers. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 581, permission of graduate coordinator.
CMPT592: Data Base Design and Implementation
To develop indepth 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 hours lecture.) 3 sh.
Prerequisites: CMPT 586, permission of graduate coordinator.
CMPT593: Structured System Design and Analysis
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 hours lecture.) 3 sh.
Prerequisites: CMPT 586, and permission of graduate coordinator.
CMPT594: Software Engineering and Reliability
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 hours lecture.) 3 sh.
Prerequisites: Permission of graduate coordinator.
CMPT596: Principles of Data Communication
Physical and logical aspects of data communications: analogdigital, broadbandbaseband, TDMFDM, protocols, modulation techniques, hardware for communication. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 580, and permission of graduate coordinator.
CMPT678: Neurocomputing
Basic neural network concepts, definitions, and building blocks; learning laws; simple implementations; associative networks; mapping networks; survey of applications. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 583, and permission of graduate coordinator.
CMPT680: Parallel Architectures and Algorithms
This course provides a study of the stateofart of parallel processing algorithms and architectures. Parallel processing uses multiple processors working together in a synchronized fashion to solve large problems fast. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 580 and CMPT 583, and permission of graduate coordinator.
CMPT683: Advanced Computer Algorithms
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. NPhard problems and NPcompleteness. (3 hours lecture.) 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
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 highquality complex software products are developed. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 594 or permission of graduate advisor.
CMPT695: Seminars in Computer Science
Guided study of selected topics in major field of interest. (14 hours seminar.) 1  4 sh.
Prerequisites: CMPT 581, 583, and 586 and permission of graduate coordinator.
CMPT696: Local Area Networks
Fundamental issues and concepts underlying Local Area Network (LAN) development via microcomputers: topology, transmission media and technology, error control, protocols. (3 hours lecture.) 3 sh.
Prerequisites: CMPT 596, and permission of graduate coordinator.
CMPT697: Master's Project in Computer Science
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 hours lecture.) 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
Historical development, paradoxes, ordered sets, SchroderBernstein theorem, axiom of choice, transfinite induction, cardinal and ordinal numbers. (3 hours lecture.) 3 sh.
Prerequisites: MATH 222 and permission of graduate program coordinator.
MATH521: Real Variables I
Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. (3 hours lecture.) 3 sh.
Prerequisites: MATH 426 and permission of graduate program coordinator.
MATH522: Real Variables II
Real number system, Lebesgue measure and integration, differentiation, Fourier series, LP, metric, normed vector, Banach and Hilbert spaces. (3 hours lecture.) 3 sh.
Prerequisites: MATH 521, permission of graduate program coordinator.
MATH525: Complex Variables I
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 hours lecture.) 3 sh.
Prerequisites: MATH 426 and permission of graduate program coordinator.
MATH526: Complex Variables II
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 hours lecture.) 3 sh.
Prerequisites: MATH 525, permission of graduate program coordinator.
MATH530: Mathematical Computing
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 hours lecture.) 3 sh.
Prerequisites: Permission of the graduate program coordinator or consent of the instructor.
MATH531: Abstract Algebra I
Basic algebraic structures including groups, rings, fields, modules and lattices. (3 hours lecture.) 3 sh.
Prerequisites: MATH 431 and permission of graduate program coordinator.
MATH532: Abstract Algebra II
Basic algebraic structures including groups, rings, fields, modules and lattices. (3 hours lecture.) 3 sh.
Prerequisites: MATH 531, permission of graduate program coordinator.
MATH535: Linear Algebra I
Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335 and permission of graduate program coordinator.
MATH536: Linear Algebra II
Vector spaces and linear transformations, including inner product, matrix representations, binary and quadratic forms, eigenvectors, canonical forms, and functions of matrices. (3 hours lecture.) 3 sh.
Prerequisites: MATH 535, permission of graduate program coordinator.
MATH537: Mathematical Logic
Propositional and predicate calculus, model theory, Godel's completeness theorems and decidability. (3 hours lecture.) 3 sh.
Prerequisites: MATH 425 and permission of graduate program coordinator.
MATH540: Probability
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 hours lecture.) 3 sh.
Prerequisites: MATH 340 and permission of graduate program coordinator.
MATH551: Topology
Basic pointset topology, topological spaces, homeomorphisms, compactness, connectedness, separation properties, uniformities, metrizability, introductory algebraic topology, homology groups and homotopy. (3 hours lecture.) 3 sh.
Prerequisites: MATH 425, and permission of graduate program coordinator.
MATH554: Projective Geometry
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 hours lecture.) 3 sh.
Prerequisites: MATH 335 and permission of graduate program coordinator.
MATH555: Differential Geometry
Application of vectors to the study of classical threedimensional geometry. Topics include: plane and space curves, first and second fundamental forms, lines of curvature, asymptotic lines, geodesics. (3 hours lecture.) 3 sh.
Prerequisites: MATH 222 and permission of graduate program coordinator.
MATH560: Numerical Analysis
Error analysis, interpolation and approximation theory, numerical solution of linear and nonlinear equations, numerical differentiation and integration, numerical solution of differential equations. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335, and permission of graduate program coordinator.
MATH564: Ordinary Differential Equation
Linear and nonlinear equations, Green's functions, power series solutions, autonomous systems, existence and uniqueness, singularities, SturmLiouville systems. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.
MATH566: Partial Differential Equations
First order equations, separation of variables, series solutions, hyperbolic, parabolic and elliptic equations, characteristics, transform methods. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335, and 420, and permission of graduate program coordinator.
MATH568: Applied Mathematics: Continuous
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 hours lecture.) 3 sh.
Prerequisites: MATH 335, and 340, and 420, and 425, and permission of graduate program coordinator.
MATH569: Applied Mathematics: Discrete
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, inclusionexclusion, the pigeonhole principle, chromatic number, eulerian chains and paths, hamiltonian chains and paths, flows in networks, finite Markov chains. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335, and 340, and 425, and permission of graduate program coordinator.
MATH580: Combinatorial Mathematics
Arrangements and selections, binomial coefficients, Stirling numbers, generating functions, recurrence relations, inclusionexclusion, Polya enumeration formula, combinatorial graph theory, combinatorial geometries. (3 hours lecture.) 3 sh.
Prerequisites: MATH 222 and graduate program coordinator's permission.
MATH581: Graph Theory
Graphs, digraphs, and trees. Connectivity, separability, planarity, and colorability. Cliques, independent sets, matchings, flows and tours. Graphs as mathematical models; graph algorithms. (3 hours lecture.) 3 sh.
Prerequisites: MATH 222, and 335, and graduate program coordinator's permission.
MATH584: Operations Research
An indepth 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 hours lecture.) 3 sh.
Prerequisites: MATH 425 and STAT 440 and permission of graduate program coordinator.
MATH590: Advanced Topics
An indepth 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 hours lecture.) 3 sh.
Prerequisites: Graduate program coordinator's permission.
MATH591: Applied Industrial Mathematics
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, costbenefit analysis, ordinary differential equations, partial differential equations, numerical methods, divided differences, splines, Galerkin's method, and finite elements. (3 hours lecture.) 3 sh.
Prerequisites: MATH 335, MATH 425, MATH 530, STAT 440 or permission of graduate program coordinator.
MATH595: 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. (14 hours seminar.) 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
Review of estimation and hypothesis testing for one sample and two sample problems; introduction to nonparametric statistics and linear regression; fundamental principles of design, completely randomized design, randomized block design, latin square, and 2 factor design. (3 hours lecture.) 3 sh.
Prerequisites: STAT 330 or STAT 443 and permission of graduate program coordinator.
STAT542: Statistical Theory I
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chisquared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, NeymanPearson 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 hours lecture.) 3 sh.
Prerequisites: STAT 541 and permission of graduate program coordinator.
STAT543: Statistical Theory II
Discrete and continuous probability distributions, multivariate distributions, sampling theory, transformations, Chisquared, 'F' and 't' distributions. Point estimation, properties of estimators, sufficiency, exponential families, interval estimation, hypothesis testing, power, NeymanPearson 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 hours lecture.) 3 sh.
Prerequisites: STAT 542 and permission of graduate program coordinator.
STAT544: Statistical Computing
Computer systems for data analysis and data graphics, and intermediate level statistical methodology are investigated. Several statistical computing packages are utilized and evaluated. (3 hours lecture.) 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: NonParametric Statistics
Selected distributionfree tests and estimation techniques including sign, KolmogorovSmirnov, Wilcoxon signed rank, MannWhitney, Chisquare, rank correlation, Kendall's Tau, KruskalWallace, Friedman, McNemar, and others. (3 hours lecture.) 3 sh.
Prerequisites: STAT 330 and permission of graduate program coordinator.
STAT547: Design and Analysis of Experiments
Fundamental principles of design; fixed, random and mixed models; factorial designs; designs with restricted randomization; splitplot design; confounding; fractional replication; experimental and sampling errors. (3 hours lecture.) 3 sh.
Prerequisites: STAT 541 or STAT 548, and permission of graduate program coordinator.
STAT548: Applied Regression Analysis
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 hours lecture.) 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT549: Sampling Techniques
Sampling and survey methodology; basic sampling theory; simple, stratified, random, cluster, systematic and area sampling. Sampling errors and estimation procedures. (3 hours lecture.) 3 sh.
Prerequisites: STAT 330 or STAT 443, and permission of graduate program coordinator.
STAT595: Topics in Statistics
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 hours lecture.) 3 sh.
Prerequisites: Permission of graduate program coordinator.
STAT640: Biostatistics I
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 hours lecture.) 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT641: Biostatistics II
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 hours lecture.) 3 sh.
Prerequisites: STAT 544, STAT 547, STAT 548, and permission of graduate program coordinator.
STAT642: Introduction to Stochastic Processes
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 hours lecture.) 3 sh.
Prerequisites: MATH 540 and permission of graduate program coordinator.
STAT645: Advanced Topics in Statistics
Recent developments in statistical science. Topics such as data mining, statistical genomics, computationally intensive dataanalytic 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 hours lecture.) 3 sh.
Prerequisites: Permission of graduate program coordinator.
STAT646: Multivariate Analysis
Analysis of multiple response variables simultaneously; covariance and the multivariate normal distribution; manova, discriminant functions; principle components and canonical correlations. (3 hours lecture.) 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 600level course, and permission of graduate program coordinator.
STAT648: Advanced Statistical Methods
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 hours lecture.) 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.