Computer Science and Statistics

College of Arts and Sciences

Course Listing and Descriptions

Next Semester Course Listings

Fall 2016 Course Listings

General Listings

The information on this page summarizes the courses offered by the department. You will also find sample syllabi attached to courses where it is available. Not all courses are available every semester, and some may only run every other year. The Univeristy Catalog is the final authority on course descriptions, and should be consulted to resolve any discrepancies.

Computer Science

Statistics

Cyber Security & Forensics

Computer Science Course Descriptions

CSC 101: Computing Concepts
LEC: (4 crs.) Capabilities and limitations of computers. Applications of computers in today’s society. Overview of computing systems and programs. Students will complete several projects using a computer. (Lec. 3, Lab. 2/Online) Not open to students who have credit in any college-level computer science course, or to computer science majors. (B3) (B4)

 

CSC 104: Puzzles + Games = Analytical Thinking
LEC: (4 crs.) Cross-listed as (CSC), MTH 104. Introduces mathematical problem solving and computational thinking through puzzles and games. Students work in small groups on activities to enhance their analytic abilities. Topics include numbers, probability, logic, algorithms, and graphs. (Lec. 4) Pre: High school mathematics. No programming required. (B3)

 

CSC 106: The Joy of Programming (Sample Syllabus)
LEC: (4 crs.) The art of problem solving through computer programming. Students explore innovative and cutting edge applications that may include mobile apps, multimedia, computer games, puzzles, robotics, graphics and animation, social networking, physical computing. (Lec. 3, Lab. 1) Pre: Not open to students with credit in CSC courses at 200-level or above. (B3)

 

CSC 110: Survey of Computer Science
LEC: (4 crs.) Broad introduction to computer science, with an emphasis on problem-solving. Algorithm discovery. Algorithm analysis. Algorithmic solutions to problem in various sub-fields including operating systems, digital forensics, computer graphics, artificial intelligence, and bioinformatics. (Lec. 3, Lab. 2) Open only to computer science majors with 4 or fewer credits in CSC courses.

 

CSC 192: Introductory Topics in Computing
LEC: (1-4 crs.) Introductory topics of current interest in computing. This course may be repeated under different topics. (Lec., Project) Pre: permission of instructor.

 

CSC 200: Computer Problem Solving For Science and Engineering
LEC: (4 crs.) An integrated symbolic, numerical, and graphical approach to computer problem solving. Structured design; fundamental programming techniques. Computer algebra systems. Scientific, engineering, and mathematical applications. (Lec. 3, Lab. 2/Online) Pre: credit or concurrent enrollment in MTH 131 or 141. Not for major credit in computer science. May not be taken for credit by students with credit in CSC 201 or 211.

 

CSC 201: Introduction to Computer Programming
LEC: (4 crs.) Computer characteristics, algorithms, data representation, program development. Students will write several programs to solve numerical and nonnumerical problems. (Lec.3, Lab. 2) Pre: MTH 111 or equivalent. May not be taken for credit by students with credit in 200 or 211. (B3)

 

CSC 211: Object-Oriented Programming (Sample Syllabus)
LEC: (4 crs.) Problem specification, solution design, and algorithm development. Object-oriented programming and program structure. Functions, selection, iteration, recursion, classes, arrays, and files. Required programs will solve numerical and nonnumerical problems. (Lec. 3, Lab. 2) Pre: prior experience with computers and programming and MTH 111 or equivalent. Intended for computer science and computer engineering majors.

 

CSC 212: Data Structures and Abstractions
LEC: (4 crs.) Abstract data types and data structures. Pointers, linked lists, stacks, queues, binary trees, and tables. Fundamentals of software engineering. Development of object-oriented programming techniques. (Lec. 3, Lab. 2/Online) Pre: CSC 211 and MTH 141. Intended for computer science and computer engineering majors.

 

CSC 292: Topics in Computing
LEC: (1-4 crs.) Topics of current interest in computing. This course may be repeated under different topics. (Lec., Project) Pre: permission of instructor.

 

CSC 301: Fundamentals of Programming Languages (Sample Syllabus)
LEC: (4 crs.) Organization of programming languages, data and control structures, syntax and semantics, compilers and interpreters. Block structured languages, recursion, parameter passing, run-time storage management. Procedural, functional, object-oriented, and logical languages. (Lec. 3, Lab. 2/Online) Pre: CSC 212.

 

CSC 305: Software Engineering (Sample Syllabus)
LEC: (4 crs.) Programming environments and methodologies for the design, development, testing, and maintenance of large software systems. Student teams will develop a substantial software product from requirements to delivery using disciplined techniques. (Lec. 3, Project 3) Pre: CSC 212.

 

CSC 320: Social Issues in Computing
LEC: (4 crs.) Discussion of the social and ethical issues created by the use of computers. The problems that computers solve and those that they produce. Ethics and responsibilities of the computer professional. (Lec. 4) Pre: CSC 211.

 

CSC 340: Applied Combinatorics
LEC: (4 crs.) Combinatorial problem-solving for computer science. Set theory and logic, proofs by induction and contradiction, elementary probability; arrangements, selections, distributions, binomials, inclusion-exclusion; recurrence relations and their solution; graph theory, trees, networks. (Lec. 4) Pre: CSC 212 and credit or concurrent enrollment in MTH 215, and student must be admitted to a degree-granting college. Student may not receive credit for this course and CSC 447.

 

CSC 392: Intermediate Topics in Computing
LEC: (1-4 crs.) Intermediate-level topics of current interest in computing. This course may be repeated under different topics. (Lec., Project) Pre: permission of instructor.

 

CSC 402: Programming Language Implementation (Sample Syllabus)
LEC: (4 crs.) Grammars and languages; lexical analysis and parsers; interpreters, translators, and virtual machines; symbol tables and type systems; code generation for real and virtual machines. Students will implement a number of interpreters, translators, and virtual machines for various small languages. (Lec. 3, Project 3) Pre: CSC 301, and student must be admitted to a degree-granting college.

 

CSC 406: Computer Graphics (Sample Syllabus)
LEC: (4 crs.) Interactive raster graphics; hardware, software, and algorithms. Point plotting, line drawing, geometrical transformations, clipping and windowing. Three-dimensional graphics including curves, surfaces, perspective, hidden objects, shading. User interfaces; graphical programming environments. (Lec. 3, Project 3) Pre: CSC 305, MTH 215 and 243, and student must be admitted to a degree-granting college.

 

CSC 411: Computer Organization
LEC: (4 crs.) Logical structure of computer systems viewed as a hierarchy of levels. Assembly language programming, assemblers, linkers, loaders. Computer architecture including digital logic, processor organization, instruction sets, addressing techniques, virtual memory, microprogramming. (Lec. 3, Project 3) Pre: CSC 301 and student must be admitted to a degree-granting college.

 

CSC 412: Operating Systems and Networks
LEC: (4 crs.) General concepts underlying operating systems and computer networks. Topics include process management, concurrency, scheduling, memory management, information management, protection and security, modeling and performance, networking and communication. (Lec. 3, Project 3/Online) Pre: CSC 301 and student must be admitted to a degree-granting college.

 

CSC 415: Introduction to Parallel Computing
LEC: (4 crs.) Programming techniques to engage a collection of autonomous processors to solve large-scale numerical and non-numerical problems. Processor interconnections. Parallel programming languages and models. Performance measures. (Lec. 3, Project 3) Pre: CSC 301, and student must be admitted to a degree-granting college. In alternate years.

 

CSC 417: Computer Communications
LEC: (3 crs.) Cross-listed as (ELE 437), CSC 417. Computer networks, layering standards, communication fundamentals, error detection and recovery, queuing theory, delay versus throughput trade-offs in networks, multiple-access channels, design issues in wide and local area networks. (Lec. 3) Pre: ((ELE 205 or 208 or CSC 211), and (ELE 436 or MTH 451 or ISE 411)), or permission of instructor.

 

CSC 418: Information and Network Security
LEC: (4 crs.) Cross-listed as (ELE), CSC 418. Elementary cryptography, public key, private key, symmetric key, authentication protocols, firewalls, virtual private networks, transport layer security, and wireless network security. (Lec. 3, Project 3) Pre: ELE 208 or MTH 362 or MTH 451 or ISE 411 or junior or senior standing in computer engineering or computer science or permission of instructor.

 

CSC 436: Database Management Systems (Sample Syllabus)
LEC: (4 crs.) Construction and management of large data systems. Data modeling, relational and object-oriented systems, main memory databases, query languages, query optimization, concurrency control, transaction management, distributed systems, disk organization, indexes, and emerging technologies. (Lec. 3, Project 3) Pre: CSC 301 or 412 or permission of instructor, and student must be admitted to a degree-granting college.

 

CSC 440: Design and Analysis of Algorithms
LEC: (4 crs.) Algorithm design and analysis, advanced data structures, computational complexity. Sorting, searching including hashing and balanced trees, string pattern matching, polynomial and matrix calculations, graph and network algorithms, NP-completeness and intractability. (Lec. 3, Project 3) Pre: CSC 340 and student must be admitted to a degree-granting college.

 

CSC 445: Models of Computation (Sample Syllabus)
LEC: (4 crs.) Abstract models of computational systems. Classical models for uniprocessor, sequential, and stored program computers. New models based on recent advances in hardware, software, and communications and their implications in practice. (Lec. 3, Project 1) Pre: CSC 340 and student must be admitted to a degree-granting college. In alternate years.

 

CSC 447: Discrete Mathematical Structures (Sample Syllabus)
LEC: (3 crs.) Cross-listed as (MTH), CSC 447. Concepts and techniques in discrete mathematics. Finite and infinite sets, graphs, techniques of counting, Boolean algebra and applied logic, recursion equations. (Lec. 3) Pre: junior standing or better in physical or mathematical sciences, or in engineering, or permission of instructor.

 

CSC 450: Scientific Computing
LEC: (4 crs.) Symbolic, numerical, and graphical approaches to mathematical computation. Pitfalls in numerical computation. Root finding. Numerical integration and differentiation. Approximation of functions. Interpolation and curve fitting. Linear systems. Ordinary differential equations. Multidimensional numerical optimization. (Lec. 3, Lab. 2) Not for graduate credit. Pre: CSC 212 and MTH 215 and 243.

 

CSC 481: Artificial Intelligence (Sample Syllabus)
LEC: (4 crs.) Theories, formalisms, techniques to emulate intelligent behavior using information processing models. Symbolic programming, search, problem solving, knowledge-based techniques, logic, and theorem proving. Optional topics: natural language processing, machine learning, and computer vision. (Lec. 3, Project 1) Pre: CSC 301 or permission of instructor, and student must be admitted to a degree-granting college.

 

CSC 491: Directed Study in Computer Science
IND: (1-4 crs.) Advanced work in computer science. Conducted as supervised individual projects. (Independent Study) Pre: permission of instructor. S/U credit.

 

CSC 492: Special Topics in Computer Science
LEC: (1-4 crs.) Advanced topics of current interest in computer science. (Lec.1-4, Project 1-3) Pre: permission of instructor.

 

CSC 499: Project In Computer Science
PRA: (4 crs.) Supervised work on a capstone project in computer science that prepares students for careers in industry and graduate study. (Practicum) Pre: advanced standing in computer science and departmental approval. Normally taken twice in two consecutive semesters. May be repeated for a maximum of 8 credits. Not for graduate credit. S/U credit.

 

CSC 501: Programming Language Semantics (Sample Syllabus)
LEC: (4 crs.) Design, analysis, implementation, and comparative study of major programming language families. Topics include procedural and block-structured languages, interpretive languages, concurrency, functional languages, object-oriented programming, logic programming, dataflow languages and machines. (Lec. 3, Project 3) Pre: CSC 301.

 

CSC 502: Theory of Compilers (Sample Syllabus)
LEC: (4 crs.) An advanced course in compiler construction covering advanced parsing techniques, compiler-writing tools, type checking and type inference, code optimization, and compiling nonstandard language features. (Lec. 3, Project 3) Pre: CSC 402. In alternate years. 505 Advanced Topics in Software

 

CSC 505: Advanced Topics in Software Engineering
LEC: (4 crs.) Lifecycle models; software development environments; project management. Metrics, performance, and testing. Paradigms for software design and architecture. Legal and ethical issues. (Lec. 3, Project 3) Pre: CSC 305. In alternate years.

 

CSC 509: Object-Oriented System Design
LEC: (4 crs.) Object-oriented design and programming, the software engineering process. Traditional and current object-oriented design methods. Software reuse. Design tools. Impact of the technology on traditional software engineering. (Lec. 3, Project 3) Pre: CSC 305 and working knowledge of an object-oriented language. In alternate years.

 

CSC 511: Advanced Computer Organization
LEC: (4 crs.) Evaluation of high-performance computer systems with respect to architectures, operating systems, and algorithms. High-speed conventional machines; array processors; multiprocessors; data flow machines; RISC architectures; VLSI-based machines. (Lec. 3, Project 3) Pre: CSC 411. In alternate years.

 

CSC 512: Topics In Distributed Systems
LEC: (4 crs.) Advanced topics in distributed systems. Networking; standard distributed computing environments. Distributed computing algorithms. Concurrency and threading. Real-time computing, scheduling, concurrency control, load allocation. (Lec. 3, Project 3) Pre: CSC 412. In alternate years.

 

CSC 519: Computer Networks
LEC: (4 crs.) Cross-listed as (ELE 543), CSC 519.Computer network architectures, data link control and access protocols for LANs, internet protocols and applications, software and hardware issues in computer communication, delay analysis, and current research in computer networking. (Lec. 4) Pre: ELE 437 or equivalent or CSC 412 or equivalent.

 

CSC 522: Bioinformatics I
LEC: (3-4 crs.) Cross-listed as (CSC), STA, MIC, BCH, CSC 522, BPS 542. Integrates computing, statistical, and biological sciences, algorithms, and data analysis/management. Multidisciplinary student research teams. Modeling dynamic biological processes. Extra project work for 4 credits. (Lec. 3, Project 3) Pre: major in a computing, statistical, or biological science or permission of instructor.

 

CSC 525: Systems Simulation
LEC: (3 crs.) Cross-listed as (ISE), CSC 525, ELE 515. Simulation of random processes and systems. Continuous and discrete simulation models. Data structures and algorithms for simulation. Generation of random variates, design of simulation experiments for optimization and validation of models and results. Selected engineering applications. (Lec. 3) Pre: CSC 212 or ISE 325, ISE 433 or ELE 509, or permission of instructor.

 

CSC 536: Topics in Data Management Systems
LEC: (4 crs.) Current research and developments in database management systems. Relational, semantic, object-oriented, real-time, distributed, heterogeneous, and logic databases. Concurrency control, security, active rules, recovery, and integrity subsystems. (Lec. 3, Project 3) Pre: CSC 436 or permission of instructor. In alternate years.

 

CSC 541: Advanced Topics In Algorithms
LEC: (4 crs.) Algorithm design techniques such as dynamic programming, greedy method, branch and bound. Linear programming; NP-completeness; graph algorithms; number theoretic algorithms; approximation algorithms for NP-complete problems; probabilistic and parallel algorithms. (Lec. 3, Project 3) Pre: CSC 440 or 445. In alternate years.

 

CSC 542: Mathematical Analysis of Algorithms
LEC: (4 crs.) Mathematical techniques for the analysis of algorithms. Sums and products; finite difference calculus; properties of binomial coefficients; Stirling, harmonic, and Fibonacci numbers; recurrence relations; generating functions; asymptotic approximation. Case studies. (Lec. 3, Project 3) Pre: CSC 440. In alternate years.

 

CSC 544: Theory Of Computation (Sample Syllabus)
LEC: (4 crs.) Finite automata, pushdown automata, formal grammars and Chomsky hierarchy, Turing machines, computability, basics of complexity theory. Advanced topics including some of the following: cryptography, interactive proofs, circuit complexity, completeness for various complexity classes, relations among complexity classes, new models of computation. (Lec. 3, Project 3) Pre: CSC 440 or 445. In alternate years.

 

CSC 547: Combinatorics
LEC: (3 crs.) Cross-listed as (MTH), CSC 547. Enumeration: generation functions, recurrence relations, classical counting numbers, inclusion-exclusion, finite set systems and designs. Polya theory, coding theory, and Ramsey theory. Finite fields and algebraic methods. (Lec. 3) Pre: MTH 316. Offered alternate fall semesters.

 

CSC 548: Graph Theory
LEC: (3 crs.) Cross-listed as (MTH), CSC 548. Basic concepts and techniques of graph theory as well as some of their applications. Topics include: connectivity, matchings, colorings, extremal problems, Ramsey theory, planar graphs, algebraic techniques. (Lec. 3) Pre: MTH 316.

 

CSC 550: Computer Algebra
LEC: (4 crs.) Symbolic mathematical computation; history, use, representation of information, algorithms and heuristics. Big number arithmetic, manipulation of polynomials and rational expressions; algebraic simplification; factoring; symbolic integration. Organization and implementation of computer algebra systems. (Lec. 3, Project 3) Pre: CSC 350, 440. In alternate years.

 

CSC 581: Special Topics in Artificial Intelligence (Sample Syllabus)
LEC: (3 crs.) Cross-listed as (CSC), ELE 581. Topics of specialized or current interest, which may change. Topics may include expert systems, natural language processing, neural network models, machine learning. AI applications in remote sensing. (Lec. 3) Pre: CSC 481 or permission of instructor. May be repeated with permission. In alternate years.

 

CSC 583: Computer Vision
LEC: (3 crs.) Cross-listed as (ELE), CSC 583. Algorithms used to extract information from two-dimensional images. Picture functions. Template matching. Region analysis. Contour following. Line and shape descriptions. Perspective transformations. Three-dimensional reconstruction. Image sensors. Interfacing. Applications. (Lec. 3) Pre: MTH 362 or equivalent.

 

CSC 590: Digital Forensics Practicum
PRA: (3 crs.) The application of digital forensics acquisition, analysis and law to real world scenarios. (Practicum 3) Pre: CSC 586.

 

CSC 591: Directed Study in Computer Science
IND: (1-4 crs.) Advanced work in computer science conducted as supervised individual projects. (Independent Study) Pre: permission of instructor. S/U credit.

 

CSC 592: Special Topics in Computer Science
LEC: (1-4 crs.) Advanced topics of current interest in computer science. (Lec. 1-4, Project 1-3) Pre: permission of instructor. May be taken more than once.

 

CSC 599: Master’s Thesis Research
IND: (1-8 crs.) Number of credits is determined each semester in consultation with the major professor or program committee. (Independent Study) S/U credit.

 

CSC 699: Doctoral Dissertation Research
IND: (1-12 crs.) Number of credits is determined each semester in consultation with the major professor or program committee. (Independent Study) S/U credit.

 

Statistics Course Descriptions

STA 220: Statistics In Modern Society (Sample Syllabus)
LEC: (3 crs.) Introductory statistics exploring and understanding data, relationships between variables, randomness and probability. (Lec. 2, Rec. 1)

 

STA 307: Introductory Biostatistics
LEC: (4 crs.) Statistical methods applicable to health sciences. Data presentation. Vital statistics and life tables. Fitting models to health data. Testing, estimation, analysis of cross-classifications, regression, correlation. (Lec. 3, Rec. 1) Pre: MTH 107 or 108 or 131 or 141 or permission. Not open to students with credit in 308 or 409.

 

STA 308: Introductory Statistics (Sample Syllabus)
LEC: (4 crs.) Descriptive statistics, presentation of data, averages, measures of variation. Elementary probability, binomial and normal distributions. Sampling distributions. Statistical inference, estimation, confidence intervals, testing hypotheses, linear regression, and correlation. (Lec. 3, Rec. 1) Pre: MTH 107 or 110 or 111 or 131 or 141 or BUS 111 or permission of instructor. Not open to students with credit in STA 307 or 409.

 

STA 409: Statistical Methods in Research I (Sample Syllabus)
LEC: (3 crs.) Same as STA 308, but is for students who have better mathematical preparation. (Lec. 3) Pre: MTH 131 or 141. Not open to students with credit in STA 307 or 308.

 

STA 411: Biostatistics II (Sample Syllabus)
LEC: (3 crs.) Cross-listed as (STA), PHP, BPS 411. An overview of statistical methods used in performing research in pharmacotherapeutics and pharmacoepidemiology. Emphasis will be on understanding both common study designs and the output from statistical analysis of data obtained from these studies. (Lec. 3) Pre: an introductory statistics course (i.e., 307) or permission of instructor.

 

STA 412: Statistical Methods in Research II
LEC: (3 crs.) Multiple linear regression and correlation analysis, curvilinear regression. Analysis of variance and covariance. Analysis of enumerative data. Some nonparametric methods. (Lec. 3) Pre: STA 307 or 308 or 409.

 

STA 491: Directed Study in Statistics
IND: (1-3 crs.) Advanced work in statistics. Conducted as supervised individual projects. (Independent Study) Pre: permission of chairperson. S/U credit.

 

STA 492: Special Topics in Statistics
LEC: (3 crs.) Advanced topics of current interest in statistics. (Lec. 3) Pre: permission of chairperson.

 

STA 501: Analysis of Variance and Variance Components
LEC: (3 crs.) Analysis of variance and covariance, experimental design models, factorial experiments, random and mixed models, estimation of variance components, unbalanced data. (Lec. 3) Pre: STA 412.

 

STA 502: Applied Regression Analysis
LEC: (3 crs.) Topics in regression analysis including subset selection, biased estimation, ridge regression, and nonlinear estimation. (Lec. 3) Pre: STA 412.

 

STA 513: Quality Systems
LEC: (3 crs.) Cross-listed as (ISE), STA 513. Topics in statistical quality control systems. Single, multiple, and sequential sampling. Design and analysis of a wide variety of statistical control systems used in conjunction with discrete and continuous data, for several kinds of data emission. (Lec. 3) Pre: ISE 411 or equivalent.

 

STA 515: Spatial Data Analysis
LEC: (3 crs.) Analysis of point patterns: visualizing, exploring, and modeling, space time clustering, correcting for spatial variation, clustering around a specific point source. Analysis of spatially continuous data: variogram analysis and Kriging methods. (Lec. 3) Pre: STA 412 or permission of instructor.

 

STA 517: Small N Designs
SEM: (3 crs.) Cross-listed as (PSY), STA 517. A survey of Small N experimental methodology appropriate for repeated observations on a single unit or individual. Methods include quasi-experimental designs, interrupted time series, and multivariate time series. Applications in applied research, particularly behavioral intervention. (Seminar) Pre: PSY 532 and 533. In alternate years.

 

STA 520: Fundamentals of Sampling and Applications
LEC: (3 crs.) Simple random sampling; properties of estimates, confidence limits. Sample size. Stratified random sampling; optimum allocation, effects of errors, and quota sampling. Regression and ratio estimates; systematic and multistage sampling. (Lec. 3) Pre: STA 308 or 409.

 

STA 522: Bioinformatics I
LEC: (3-4 crs.) Cross-listed as (CSC), STA, MIC, BCH, CSC 522, BPS 542. Integrates computing, statistical, and biological sciences, algorithms, and data analysis/management. Multidisciplinary student research teams. Modeling dynamic biological processes. Extra project work for 4 credits. (Lec. 3, Project 3) Pre: major in a computing, statistical, or biological science or permission of instructor.

 

STA 532: Experimental Design
LEC: (3 crs.) Cross-listed as (STA), PSY, AFS 532. Application of statistical methods to biological and psychological research and experimentation. Experimental situations for which various ANOVA and ANCOVA designs are most suitable. (Lec. 3) Pre: STA 409 or equivalent.

 

STA 535: Statistical Methodology in Clinical Trials
LEC: (3 crs.) Bioavailability, dose response models, crossover and parallel designs, group sequential designs, survival analysis, meta analysis. (Lec. 3) Pre: STA 409, 411, or 412 or permission of instructor.

 

STA 536: Applied Longitudinal Analysis
LEC: (3 crs.) Longitudinal Data, Linear Mixed Effects Models, Repeated Measures ANOVA, Generalized Linear Models for Correlated Data. (Lec. 3) Pre: STA 411 or STA 412 or permission of instructor.

 

STA 541: Multivariate Statistical Methods (Sample Syllabus)
LEC: (3 crs.) Review of matrix analysis. Multivariate normal distribution. Tests of hypotheses on means, Hotelling’s T2, discriminate functions. Multivariate regression analysis. Canonical correlations. Principal components. Factor analysis. (Lec. 3) Pre: STA 412.

 

STA 542: Categorical Data Analysis Methods
LEC: (3 crs.) Analysis of multidimensional categorical data by use of log-linear and logit models. Discussion of methods to estimate and select models followed by examples from several areas. (Lec. 3) Pre: STA 412.

 

STA 545: Bayesian Statistics
LEC: (3 crs.) Introduces Bayesian methods for a variety of statistical problems. Topics include Bayesian inference, model selection, Bayesian computation, hierarchical models and Gibbs sampling. Open-source software will be utilized for Bayesian data analyses. (Lec. 3) Pre: STA 411 or STA 412 or permission of instructor.

 

STA 550: Ecological Statistics (Sample Syllabus)
LEC: (3 crs.) Application of statistical methodology to the following topics: population growth, interactions of populations, sampling and modeling of ecological populations, spatial patterns, species abundance relations, and ecological diversity and measurement. (Lec. 3) Pre: STA 409 or permission of instructor.

 

STA 576: Econometrics
LEC: (4 crs.) Cross-listed as (EEC), ECN, STA 576. Application of statistics and mathematics to economic analysis. Implication of assumption required by statistical methods for testing economic hypotheses. Current econometric methods examined and discussed. (Lec. 3, Lab. 2) Pre: ECN 575 or equivalent, STA 308 or equivalent, or permission of instructor.

 

STA 584: Pattern Recognition
LEC: (3 crs.) Cross-listed as (ELE), STA 584. Random variables, vectors, transformations, hypothesis testing, and errors. Classifier design: linear, nonparametric, approximation procedures. Feature selection and extraction: dimensionality reduction, linear and nonlinear mappings, clustering, and unsupervised classification. (Lec. 3) Pre: ELE 509 or introductory probability and statistics, and knowledge of computer programming.

 

STA 591: Directed Study in Statistics
IND: (1-3 crs.) Advanced work in experimental statistics conducted as supervised individual projects. (Independent Study) Pre: permission of chairperson. S/U credit.

 

STA 592: Special Topics in Statistics
LEC: (3 crs.) Advanced topics of current interest in statistics. (Lec. 3) Pre: permission of chairperson. May be taken more than once.

 

STA 599: Master’s Thesis Research
IND: (1-6 crs.) Number of credits is determined each semester in consultation with the major professor or program committee. (Independent Study) S/U credit.

 

STA 612: Structural Modeling
LEC: (3 crs.) Cross-listed as (PSY), STA 612. Theory and methodology of path analysis with latent variables. Discussion of “causation” and correlation, Confirmatory Factor Analysis, Measurement and Structural Equation models. Practical applications using current computer programs (e.g. EQS). (Lec. 3) Pre: PSY 533 or 610.

 

In addition to statistics courses offered by the Department of Computer Science and Statistics under the STA code, there are a number of statistics-oriented courses offered by other departments:

Business

210 Managerial Statistics I
212 Managerial Statistics II
461 Forecasting

Psychology

300 Quantitative Methods in Psychology
533 Advanced Quantitative Methods in Psychology

Master of Business Administration

500 Statistical Methods for Management
582 Applied Time Series Methods and Business Forecasting

Industrial and Systems Engineering

411 Probability and Statistics for Engineers
412 Statistical Methods for Engineers
533 Advanced Statistical Methods for Research and Industry
634 Design and Analysis of Industrial Experiments

Mathematics

451 Introduction to Probability and Statistics
452 Mathematical Statistics
550 Probability and Stochastic Processes
551 Mathematical Statistics

Cyber Security & Forensics Course Descriptions

 

CSF 102: Fundamentals for Cyber Security (Sample Syllabus)
ONL: (4 crs.) This course provides an overview of the technical background required to provide solutions to many cyber security problems. This background includes: binary/hex number systems, operating systems concepts, file systems, OSI model, network topologies and protocols, and wireless standards and implementations. (Online)

 

CSF 410: Digital Forensics I (Sample Syllabus)
ONL: (4 crs.) The science, technology, procedures, and law of acquiring and analyzing digital evidence from computers and devices. (Online 4) Pre: CSF 102 or permission of instructor.

 

CSF 412: Digital Forensics II
ONL: (4 crs.) Selected focused topics on acquiring and analyzing evidence from digital devices. Details on analysis of specific operating system artifacts. (Online) Pre: CSF 410. Not for graduate credit.

 

CSF 414: Digital Forensics Analysis
ONL: (4 crs.) Digital forensics analysis of evidence using the leading industrial tools. Key word searching, filtering, and report generation. (Online 4) Pre: CSF 410.

 

CSF 424: Live Forensics and Incident Response
ONL: (4 crs.) Introduces concepts and skills necessary to conduct investigations of compromised workstations and servers. Presents techniques to determine necessary steps to take for proper containment, evidence collection, analysis and restoration. (Online) Pre: CSF 432 or CSF 410.

 

CSF 430: Introduction to Information Assurance (Sample Syllabus)
ONL: (4 crs.) Fundamental concepts to understand threats to security; various defenses against those threats. Planning for security; technology used to defend computer systems; implementing security measures and technology. (Online 4) Pre: CSF 102 or permission of instructor.

 

CSF 432: Introduction to Network and Systems Security
ONL: (4 crs.) This course provides an overview of network and systems security. It provides the underlying theory of computer security. It further introduces hands-on skills and techniques that are essential to effectively secure the networks and systems of large and small organizations. (Online 4) Pre: CSF 102 or permission of instructor.

 

CSF 434: Network and Systems Security (Sample Syllabus)
ONL: (4 crs.) Advanced security topics including intrusion detection, penetration testing, incident response, malware analysis, and risk management. (Online) Pre: CSF 432. Not for graduate credit.

 

CSF 512: Advanced Digital Forensics
ONL: (4 crs.) New and emerging techniques for identifying, acquiring, and analyzing new and emerging sources of digital evidence. Current research in Digital Forensics. (Online 4) Pre: CSF 410.

 

CSF 516: File System Analysis
ONL: (4 crs.) The structure and implementation of computing device file systems. Forensic analysis and reconstruction of digital evidence found in modern file systems. (Online 4) Pre: CSF 410.

 

CSF 524: Advanced Incident Response
ONL: (4 crs.) Presents advanced techniques and research for incident response and live forensics. Topics may include live forensics in cloud environments, visualization of security incidents, and live forensics in the smart grid. (Online) Pre: CSF 432 or CSF 410.

 

CSF 534: Advanced Topics in Network and System Security (Sample Syllabus)
ONL: (4 crs.) Advanced topics in network security including intrusion detection, penetration testing, incident response, malware analysis, and risk management. Students will learn relevant skills and research emerging solutions to these problems. (Online 4) Pre: CSF 432.

 

CSF 536: Advanced Intrusion Detection and Defense
ONL: (4 crs.) Presents advanced techniques and research on intrusion detection and network defense. Topics may include network traffic analysis, intrusion analysis, machine learning techniques for intrusion detection, data mining for intrusion detection, advanced persistent threats. (Online 4) Pre: CSF 432.

 

CSF 538: Penetration Testing (Sample Syllabus)
ONL: (4 crs.) Advanced techniques used in assessing the security of networks and identifying vulnerabilities. Network traffic analysis; session hijacking; social engineering; application exploitation; rootkits; network sniffers; developing threats. (Online 4) Pre: CSF 432

 

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