Computer Science (M.S.) - Graduate (Combined B.S./M.S.) - 2009 University Catalog
You are viewing the 2009 University Catalog. Please see the newest version of the University Catalog for the most current version of this program's requirements.
COMPUTER SCIENCE MAJOR REQUIREMENTS
Complete 33 semester hours including the following 5 requirement(s):
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REQUIRED CORE
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 694 Software Quality Assurance 3 -
REQUIRED TWO-COURSE SEQUENCE
Complete 1 of the following sequences for 6 semester hours:
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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 -
VISUAL COMPUTING SPECIALIZATION
Complete
CMPT 574 Pixel and Image Processing 3 CMPT 575 Introduction to Computer Graphics 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 requirement(s):
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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 OPTIONS
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 -
COMPREHENSIVE EXAM
Successfully complete the Comprehensive Exam.
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COMBINED PROGRAM REQUIREMENT
In order to graduate, the combined portion of the program must be completed. Contact the Departmental Advisor.
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 sh.
Prerequisites: CMPT 580 and permission of graduate coordinator.
CMPT575: Introduction to Computer Graphics
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
CMPT699: Master's Thesis Extension
Continuation of Master's Thesis Project. Thesis extension will be graded as IP (In Progress) until thesis is completed, at which time a grade of Pass or Fail will be given. 1 sh.
Prerequisites: CMPT 698.
MATH520: Set Theory
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
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
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
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
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
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
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
Basic algebraic structures including groups, rings, fields, modules and lattices. 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 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 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 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 sh.
Prerequisites: MATH 340 and permission of graduate program coordinator.
MATH551: Topology
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
MATH698: 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 MATH 699 if they don't complete MATH 698 within the semester. 3 sh.
Prerequisites: Permission of graduate program coordinator.
MATH699: Master's Thesis Extension
Continuation of Master's Thesis Project. Thesis extension will be graded IP (In Progress) until thesis is completed, at which time a grade of Pass or Fail will be given. 1 sh.
Prerequisites: MATH 698, permission of graduate program coordinator.
STAT541: Applied Statistics
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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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