Management Science and Information Systems

22:135:571 Calculus for Managers (2) Topics include functions, lines, quadratic equations, exponential and logarithmic functions, limits, derivatives, partial derivatives, one and two variable function optimization, Lagrange multipliers, matrix algebra, and solutions to linear equations.

22:135:572 Statistics for Managers (2) Topics include descriptive statistics, elementary probability, discrete distributions, normal distributions, sampling distributions, small and large sample inference for an unknown population mean, and proportions.

22:198:504 Introduction to Information Technology (1) A survey of the use and management of information technology in business. Students will acquire a basic familiarity with information technology, including database technology, telecommunications, the internet, and applications to marketing. They will also study the dynamics of the information technology industry.

22:198:603 Database Systems (3) The purpose of this course is to provide students with an understanding of database technology and its application in managing data resources. The conceptual, logical, and physical design of databases will be analyzed. A database management system such as ORACLE or INGRES will be used as a vehicle for illustrating some of the concepts discussed in the course. Prerequisite: Background in a procedurally oriented language (C preferred) or permission of the instructor.          

22:198:604 Computers and Information Systems (3) This general concepts course provides an understanding of the hardware, software, and other components of computer systems; it surveys file and database management systems, telecommunications and networks, analysis, design and development of computer-based information systems, and evaluation of computer acquisitions. This course is an alternative to 22:198:605 Introduction to Software Development.

22:198:605 Introduction to Software Development (3) Fundamentals of the C/C++ programming language comprise a major part of this course.  Introduces students to procedural and object-oriented programming. Topics from data storage, systems analysis, and database systems are also covered.

22:198:608 Distributive Information Systems and Telecommunications (3) Surveys the current state and future direction of data communication and teleprocessing systems. Through cases and case studies, provides the concepts and terminology of teleprocessing systems, networking, distributed processing, protocols, etc. Emphasis placed on planning, component selection, operation, and management of cost-effective data communication. Prerequisites: Completion of the management information systems (MIS) breadth requirement, and a background in a procedurally oriented language (C or Pascal preferred); or permission of the instructor.       

22:198:609 Information Technology for Managers (3)

22:198:610 Electronic Commerce (3) Electronic commerce (EC) refers to business activities involving consumers, manufacturers, service providers, and intermediaries using computer networks such as the internet. The goals of EC are to reduce product and service costs and improve customer response time and quality. Hence, implementing initiatives in electronic commerce has emerged as a significant business strategy in the information age. This course serves as an introduction to EC. It discusses the three principle tenets of this discipline: business, technical, and policy issues.  Specifically, it covers the various components and services of EC, technologies involved in EC, and EC for business applications.

22:198:611 Security for Electronic Commerce (3) The objective of this course is to introduce to students the emerging area of electronic commerce (EC) and the security challenges and threats in EC, and provide them with an understanding of the state-of-the-art EC security technologies. In particular, this course discusses security requirements for electronic commerce such as identification and authentication, authorization and access control, data integrity, confidentiality, nonrepudiation, trust, and regulation. Discusses various security standards including network security architecture standards, data encryption standards, data integrity standards, digital signature standards, authentication standards, certification standards, electronic data interchange standards, and electronic mail standards. It also discusses the emerging internet standards, firewalls, public key cryptography standards, Java security, Lotus Notes security, database security, security payments such as SET (secure electronic transaction), digital cash and digital checks, and smart card technology.

22:198:640 Object-Oriented Concepts and Applications (3)

22:198:658 Emerging Information Technologies (3) This course presents an introduction to emerging technologies. It focuses on the use of technology to support decision making, facilitate cooperation, and enable the information infrastructure. Examples of covered topics are: new hardware innovations, search engines, data warehousing, media appropriateness, electronic commerce methods, virtual teams in organizations, and client/server systems.
Prerequisite: A fundamental knowledge of computers and information systems.

22:960:575 Data Models (3) Introduces statistics as applied to managerial problems. Emphasis is on conceptual understanding as well as conducting statistical analyses. Students learn the limitations and potential of statistics, gain hands-on experience using Excel, as well as comprehensive packages, such as SPSSŪ. Topics include descriptive statistics, continuous distributions, confidence intervals for means and proportions, and regression. Application areas include finance, operations, and marketing. Introduces the basic concepts of model building and its role in rational decision making. Knowledge of specific modeling techniques, such as linear and nonlinear programming, decision analysis, and simulation, along with some insight into their practical application is acquired. Students are encouraged to take an analytic view of decision making by formalizing trade-offs, specifying constraints, providing for uncertainty, and performing sensitivity analyses. Students form groups to collect and analyze data, and to write and present a final report. Prerequisite: 22:135:572 with grade of B or better.      

22:960:576 Statistical Models (3) Introduces estimation and testing problems using simple and multiple regression models. These techniques are applied to model building involving quantitative and/or qualitative independent variables. Topics in experimental design and analysis of variance, piecewise linear regression, weighted least squares, and logistic regression are introduced. Transformation of data, multicolinearity, partial correlation, and residual and influence analysis are discussed. Also included is an introduction to the analysis of contingency tables and survey methods. Computers are used extensively in the statistical analysis of data using the techniques covered in this course. Prerequisite: Fulfillment of statistics qualifying requirement.        

26:198:621 Electronic Commerce (3) This course will cover the theoretical foundations, implementation problems, and research issues of the emerging area of electronic commerce. It will discuss technological, conceptual, and methodological aspects of electronic commerce. The list of topics to be covered  includes: fundamentals of internet technology, pricing of and accounting for internet transport, security problems of the internet, electronic payment systems, online financial reporting and auditing, intelligent agents, web measurements, electronic markets, and value chain over the internet. The coursework will include presentations of research articles, in-class discussions, and a final course project researching one of the problems of electronic commerce.
Prerequisites: Basic computer literacy; introductory courses in computer information systems and economics.

26:198:622 Expert Systems (3) Basic theory of rule-based systems and Bayes networks. Alternative architectures for managing uncertainty. Use of probabilistic logic to model causality. Related ideas from machine learning, neural networks, and genetic algorithms. Applications to auditing, marketing, and production.

26:198:641 Applications of Database Systems (3) Emphasizes the functions of database administrator. Includes survey of physical and logical organization of data and their methods of accessing, and the characteristics of different models of generalized database management systems. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.        

26:198:642 Multimedia Information Systems (3) This course covers principal topics related to multimedia information systems. These include organizing multimedia content, physical storage and retrieval of multimedia data, content-based search and retrieval, creating and delivering networked and multimedia presentations, and current research directions in this area. Prerequisite: A master's-level course in databases such as 22:198:603 or NJIT CIS 631.        

26:711:561 Mathematical Methods for Economics (3) Explores the quantitative tools and principles used to model operational procedures in economic and business systems: types of variables, mathematical sets, and functional forms in constrained and unconstrained optimization. Other topics include tractability, duality, Kuhn-Tucker theory, algorithms, and computation. Prerequisite: Differential calculus.

26:711:651 Linear Programming (3) A survey of linear programming and its applications. Topics include linear programming models, basic simplex method, duality theory and complementary slackness, sensitivity analysis, degeneracy, matrix notation and revised simplex method, special linear programs such as transportation and network flow theory, applications in statistics, economics and finance models of linear programming, game theory, and introduction to interior point methods. Prerequisite: Undergraduate linear algebra.

26:711:652 Nonlinear Programming (3) Fundamentals of nonlinear optimization, with an emphasis on convex problems. Gradient, Newton, and other methods for unconstrained problems. Projection, linearization, penalty, barrier, and augmented Lagrangian methods for constrained problems. Lagrangian functions and duality theory. Assignments include computer programming and mathematical proofs. Prerequisite: 26:711:651.

26:960:575 Introduction to Probability (3) Foundations of probability. Discrete and continuous simple and multivariate probability distributions; random walks; generating functions; linear functions of random variable; approximate means and variances; exact methods of finding moments; limit theorems; stochastic processes including immigration-emigration, simple queuing, renewal theory, and Markov chains. Prerequisite: Undergraduate or master's-level course in statistics.        

26:960:577 Introduction to Statistical Linear Models (3) Linear models and their application to empirical data. The general linear model; ordinary-least-squares estimation; diagnostics, including departures from underlying assumptions, detection of outliners, effects of influential observations, and leverage; analysis of variance, including one-way layouts, two-way, and higher dimensional layouts, partitioning sums of squares, and incomplete layouts (Latin squares, incomplete blocks, and nested or repeated measures). Emphasizes computational aspects and use of standard computer packages such as SAS. Prerequisite: Undergraduate or master's-level course in statistics.      

26:960:580 Stochastic Processes (3) Review of probability theory with emphasis on conditional expectations; Markov chains; the Poisson process; continuous-time Markov chains; renewal theory; queuing theory; and introduction to stochastic calculus, e.g., Ito's Lemma. Prerequisite: 26:960:575.