The department offers courses in the areas of computer information systems (CIS), operations research, and statistics. Courses in each of these areas provide training in problem solving techniques useful in gaining strategic advantage in the marketplace. CIS students are afforded the opportunity to gain a strong foundation in the business, managerial, and technical issues related to information systems with courses in programming, data management, telecommunications, the Internet and e-commerce, and the analysis and design of computer-based solutions to business problems. Operations research trains students in the application of mathematical models and decision making for business, industry, and government with an emphasis on modeling methods, analysis, and implementation relevant to operational and management planning issues. Statistics students are provided with a skills base for the application of statistical techniques and tools to a wide variety of areas, including computational statistics, sample survey, experimental design, and quantitative methods in marketing.
General Information
The Department of Statistics and Computer Information Systems offers majors in the fields of computer information systems and statistics and quantitative modeling.
The computer information systems area prepares professionals in the development and use of computer-based technologies to develop systems that fulfill business information needs. Baruch's program trains students to analyze business needs and to design, implement, and use information systems to satisfy those needs.
The operations research area provides basic preparation for students who wish to pursue careers in the decision sciences and provides fundamental quantitative knowledge required by those who major in other business areas. Emphasis is placed on modeling methods, analysis, and implementation relevant to operational and management planning issues in many business areas, including marketing, production, finance, accounting, and information technology.
The statistics area not only provides the basic preparation for students who wish to pursue careers in statistics but also provides the quantitative knowledge required by those who major in other business areas. Statistics and quantitative modeling majors are provided with the base for the application of statistical techniques to a wide variety of fields.
The CIS program provides a strong foundation in the business and managerial issues related to information systems. Computer information systems are presented in light of their role as tools for strategic advantage in the marketplace. To facilitate this, course offerings provide computer, technological, and problem - solving skills. The CIS program addresses such areas as CASE (computer-assisted software engineering), networks and telecommunications, electronic commerce, the Internet, client-server technology, and object-oriented technologies.
Program Learning Goals
| Database Development | Students will apply the principles of design and development of relational databases. |
| System Analysis and Design | Students will elicit, analyze, and model system requirements. |
| Software Programming | Students will implement software systems using a suitable programming language/development environment. |
| Information Technology Management | Students will identify and explain the factors that contribute to the successful design, implementation, and management of Information Technology systems in organizations. |
General CIS TrackRequired Courses 15 credits | |||||
| Programming and Computational Thinking | 3 credits | |||
Choose from
or
or
| Object Oriented Programming I, or Object Oriented Programming with Java, or Programming for Analytics |
3 credits | |||
| Database Management Systems | 3 credits | |||
| Systems Analysis and Design | 3 credits | |||
| Information Technology Development and Project Management | 3 credits | |||
At at least 3 credits should be from a course at the 4000 level | |||||
| Object Oriented Programming I | 3 credits | |||
| Object Oriented Programming with Java | 3 credits | |||
| Programming for Analytics | 3 credits | |||
| Introduction to Semantic Technologies | 3 credits | |||
| Blockchain Technologies and Applications | 3 credits | |||
| Spreadsheet Applications in Business | 3 credits | |||
| e-Business Technologies | 3 credits | |||
| Networks and Telecommunications I | 3 credits | |||
| Cybersecurity | 3 credits | |||
| Principles of Web Design | 3 credits | |||
| Green IT | 3 credits | |||
| Foundations of Business Analytics | 3 credits | |||
| Social Media Technologies in Organizations | 3 credits | |||
| Usability, Privacy, and Security | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Special Topics in Computer Information Systems | 3 credits | |||
| Object-Oriented Programming II | 3 credits | |||
| Web Applications Development | 3 credits | |||
| Data Visualization | 3 credits | |||
| Information Technology Audit | 3 credits | |||
| Data Warehousing for Analytics | 3 credits | |||
| Networks and Telecommunications II | 3 credits | |||
| Ethical Hacking | 3 credits | ||||
| Expert (Knowledge-Based) Systems and Related Technologies | 3 credits | |||
| FinTech: Principles and Applications | 3 credits | |||
| Operating Systems Concepts | 3 credits | |||
| Quantitative Methods for Accounting* | 3 credits | |||
| Quantitative Decision Making for Business I* | 3 credits | |||
| Advanced Data Mining | 3 credits | |||
* Students may not receive credit for both OPR 3450 and OPR 3300. ** Students receiving credit for MGT 3500 (Introduction to Management Science) will not receive credit for OPR 3450. † If you have used one of these programming courses (CIS 3100, CIS 3110, CIS 3120) as a required course, you may use the others as electives. | |||||
Data Analytics TrackRequired Courses (15 credits) | |||||
| Programming and Computational Thinking | ||||
| Programming for Analytics | 3 credits | |||
| Database Management Systems | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Data Warehousing for Analytics | 3 credits | |||
Elective Courses (9 credits) Choose three (3) courses of 3 credits each from the following, at least one of which should be a CIS course and one should be a STA course or an OPR course.
| |||||
| Object Oriented Programming I | 3 credits | |||
| Introduction to Semantic Technologies | 3 credits | |||
| Foundations of Business Analytics | 3 credits | |||
| Special Topics in CIS (with permission) | 3 credits | |||
| Data Visualization | 3 credits | |||
| Business Statistics II | 3 credits | |||
| Regression and Forecasting Models for Business Applications | 3 credits | |||
| Advanced Data Mining | 3 credits | |||
| Quantitative Methods for Accounting* | ||||
| Quantitative Decision Making for Business I | 3 credits | |||
| Quantitative Decision Making for Business II | 3 credits | |||
| Marketing Web Analytics and Intelligence | 3 credits | |||
| Marketing Analytics | 3 credits | |||
* Students may not receive credit for both OPR 3450 and OPR 3300. ** Students receiving credit for MGT 3500 (Introduction toManagement Science) will not receive credit for OPR 3450. | |||||
Information Risk Management and Cybersecurity TrackRequired Courses (15 credits) | |||||
| Programming and Computational Thinking | 3 credits | |||
| Database Management Systems | 3 credits | |||
| Networks and Telecommunications I | 3 credits | |||
| Cybersecurity | 3 credits | |||
| Information Technology Audit | 3 credits | |||
Elective Courses (9 credits) At least 6 credits must be from the CIS courses | |||||
| Object Oriented Programming I | 3 credits | |||
| Object Oriented Programming with Java | 3 credits | |||
| Programming for Analytics | 3 credits | |||
| Social Media Technologies in Organizations | 3 credits | |||
| Usability, Privacy, and Security | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Special Topics in CIS (with a departmental permission) | 3 credits | |||
| Object-Oriented Programming II | 3 credits | |||
| Web Applications Development | 3 credits | |||
| Networks and Telecommunications II | 3 credits | |||
| Ethical Hacking | 3 credits | ||||
| Financial Information Technologies | 3 credits | |||
| Systems Analysis and Design | 3 credits | |||
| Law and the Internet | 3 credits | |||
| Financial Regulation of Emerging Technologies | 3 credits | |||
| Corporate Compliance, Governance & Whistleblowing | 3 credits | |||
The statistics and quantitative modeling major is designed to develop quantitative thinking skills that are invaluable in business. The student will take courses from a variety of quantitative disciplines that focus extensively on statistical methodology, mathematical modeling, and computer implementation issues applied to business. The use of the computer for the solution and analysis of business problems is an integral part of the program. Graduates of this program will have a broad foundation in statistics or quantitative modeling and will be well positioned for the analysis and solution of decision problems facing business and industry in the 21st century.
It is essential that the student consult with an area advisor to plan a program prior to taking any courses in the major.
Program Learning Goals
| Quantitative Thinking Skills | Students will be able to apply the quantitative thinking and the mathematical modeling process to solve real-world problems |
| Data Analysis | Students will be able to identify appropriate methodology, conduct analysis, and interpret results |
| Deterministic Modeling Methods | Students will be able to model deterministic mathematical programming problems |
| Probabilistic Modeling Methods | Students will be able to model probabilistic problems dealing with decision analysis and simulation |
| Statistical Modeling | Students will be able to model statistical problem applied to business |
| Technological Skills | Students will be proficient in appropriate software to solve problems in statistics and quantitative modeling |
| Communication Skills | Students will be able to effectively communicate statistical and quantitative modeling methods for decision making to technical and non-technical audiences |
| Required Courses (12 credits) | ||||
| Statistical Computing | 3 credits | ||
| Quantitative Decision Making for Business I | 3 credits | ||
| Business Statistics II | 3 credits | ||
| Regression and Forecasting Models for Business Applications | 3 credits | ||
Elective Courses (12 credits) (No more than six credits outside of the CIS, OPR, STA and MTH) | ||||
| Programing and Computational Thinking | 3 credits | ||
| Object Oriented Programing | 3 credits | ||
| Programing for Analytics | 3 credits | ||
| Database Management Systems I | 3 credits | ||
| Object-Oriented Programming II | 3 credits | ||
| Data Warehousing for Analytics | 3 credits | ||
| Quantitative Decision Making for Business II | 3 credits | ||
| Bayesian Statistical Inference and Decision Making | 3 credits | ||
| Special Topics in Operations Research | 3 credits | ||
| Independent Study and Research in Operations Research | 3 credits | ||
| Data Mining for Business Analytics | 3 credits | ||
| Introduction to SAS Programming | 3 credits | ||
| Design and Analysis of Experimental Data | 3 credits | ||
| Analysis of Time Series | 3 credits | ||
| Data Visualization | 3 credits | ||
| Special Topics in Applied Statistics | 3 credits | ||
| Advanced Data Mining | 3 credits | ||
| Independent Study in Statistics | 3 credits | ||
| Marketing Research | 3 credits | ||
| Marketing Web Analytics and Intelligence | 3 credits | ||
| Marketing Analytics | 3 credits | ||
| Intermediate Calculus | 4 credits | ||
| ** Any MTH 4000 and above is also accepted as an elective | ||||
Note: OPR 3300 Quantitative Methods for Accounting may be substituted for OPR 3450 with the approval of the area advisor. | ||||
Statistics: BA Major
Statistical methods are crucial in numerous fields such as biology, physics, climate science, and finance, to name a few. The Bachelor of Arts in Statistics major is intended to provide students with fundamental knowledge and skills in probability, mathematical statistics, data analysis, and statistical computing. Students will explore the mathematical foundations of the theory of statistics. The demand for these skills has increased with the rise of big data. This major is intended to prepare students for graduate study in statistics or related subjects or for a career in data analysis or other related fields.
Please Note:
Program Prerequisites | ||
As a preliminary requirement, students must complete the following courses: | ||
Business Statistics I | 3 credits | |
Calculus III | 4 credits | |
| or |
|
Elements of Calculus III | 5 credits | |
| or |
|
Calculus III and Vector Calculus | 4 credits | |
| ||
Required Courses: |
| |
Linear Algebra and Matrix Methods | 3 credits | |
Introduction to Probability** | 4 credits | |
Mathematics of Inferential Statistics | 4 credits | |
Statistical Computing | 3 credits | |
Data Mining for Business Analytics | 3 credits | |
| Regression and Forecasting Models for Business Applications | 3 credits |
or |
|
|
| Mathematics of Data Analysis | 4 credits |
| ||
NOTES: * Students can receive credit for only one of these two courses. ** Students who have completed | ||
| ||
Students must take one of the following courses: *** | ||
Advanced Data Mining | 3 credits | |
Analysis of Time Series | 3 credits | |
Introduction to SAS Programming | 3 credits | |
Quantitative Decision Making for Business I | 3 credits | |
|
|
|
*** These courses may also be used as electives for the major | ||
|
|
|
Electives Students must complete one additional course from the following list: | ||
Bridge to Higher Mathematics | 3 credits | |
Mathematical Analysis I | 3 credit | |
Advanced Calculus II | 3 credits | |
Topology | 3 credits | |
Ordinary Differential Equations | 3 credits | |
Numerical Methods for Differential Equations in Finance | 4 credits | |
Introduction to Stochastic Process | 4 credits | |
Computational Methods in Probability | 3 credits | |
Graph Theory | 3 credits | |
Mathematical Modeling * | 3 credits | |
Combinatorics | 3 credits | |
Theory of Numbers | 3 credits | |
Elements of Modern Algebra | 3 credits | |
Introduction to Modern Geometry | 3 credits | |
History of Mathematics | 3 credits | |
Differential Geometry * | 3 credits | |
Algorithms, Computers and Programming II | 3 credits | |
Methods of Numerical Analysis | 3 credits | |
Introduction to Mathematical Logic | 3 credits | |
Fundamental Algorithms | 3 credits | |
Theory of Interest | 3 credits | |
Actuarial Mathematics I | 4 credits | |
Actuarial Mathematics II | 4 credits | |
Short-Term Insurance Mathematics | 4 credits | |
Introductory Financial Mathematics | 4 credits | |
Data Analysis and Simulation for Financial Engineers | 4 credits | |
Advanced Calculus III * | 3 credits | |
Theory of Functions of a Complex Variable | 3 credits | |
Theory of Functions of Real Variables * | 3 credits | |
Partial Differential Equations and Boundary Value Problems * | 4 credits | |
Stochastic Calculus for Finance | 4 credits | |
Programming and Computational Thinking | 3 credits | |
Object-Oriented Programming | 3 credits | |
Programming for Analytics | 3 credits | |
Database Management Systems I | 3 credits | |
Object-Oriented Programming II | 3 credits | |
Data Warehousing for Analytics | 3 credits | |
Quantitative Decision Making for Business I | 3 credits | |
Quantitative Decision Making for Business II | 3 credits | |
Bayesian Statistical Inference and Decision Making | 3 credits | |
Special Topics in Operations Research | 3 credits | |
Independent Study and Research in Operations Research | 3 credits | |
Introduction to SAS Programming | 3 credits | |
Design and Analysis of Experimental Data | 3 credits | |
Analysis of Time Series | 3 credits | |
Data Visualization | 3 credits | |
Special Topics in Applied Statistics | 3 credits | |
Advanced Data Mining | 3 credits | |
Independent Study in Statistics | 3 credits | |
|
|
|
* These courses are offered infrequently, subject to student demand. | ||
Equivalent courses in the arts and sciences and business curricula:
| The following pairs of courses are considered as equivalent for purposes of credits. Students can be given credit for either course but not for both: | ||
and
| ||
and
| ||
and
| ||
| ||
|
Return to Statistics: BA Major
General Information
The Department of Information Systems and Statistics offers five minor concentrations*. Each is outlined below:
* Optional second minors open only to students pursuing a major within the Zicklin School of Business
| Computer Applications in Business (9 credits) This minor is designed to prepare students majoring in other areas of business to be competent end users and decision makers in a computer information systems environment. The focus is on using microcomputers and higher-level applications software to implement useful applications in a wide range of business areas. | |||||
Required Courses Three courses (9 credits) from any of the following:
| |||||
Cybersecurity and Information Assurance (9 credits) This minor would provide an opportunity for students majoring in various areas of business to develop basic understanding of information security and assurance issues that organizations face today and the potential solutions available. | |||||
| Required Courses (6 credits) | |||||
| Networks and Telecommunications I | 3 credits | |||
| Cybersecurity | 3 credits | |||
| Elective Courses (3 Credits) | |||||
| Information Technology Audit | 3 credits | ||||
| Ethical Hacking | 3 credits | ||||
Data Analytics (9 credits) This minor would provide an opportunity for students majoring in various areas of business to develop basic data literacy and to integrate techniques and solutions from the areas of technology, statistics, and quantitative modeling in developing business intelligence to facilitate organizational decision-making | |||||
| Required Courses (6 credits) | |||||
| Programming and Computational Thinking | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Elective Courses (3 credits) - Choose one course from the following list. | |||||
| Programming for Analytics | 3 credits | |||
| Database Management Systems | 3 credits | |||
| Data Visualization | 3 credits | |||
| Data Warehousing for Analytics | 3 credits | |||
| Business Statistics II | 3 credits | |||
| Regression and Forecasting Models for Business Applications | 3 credits | ||||
| Marketing Web Analytics and Intelligence | 3 credits | |||
| Marketing Analytics | 3 credits | |||
or
| Business Decision Models
Quantitative Decision Making for Business I | 3 credits
3 credits | |||
| * Students receiving credit for MGT 3500 will not also receive credit for OPR 3450. | |||||
Quantitative Methods and Modeling (9 credits) The minor in quantitative methods and modeling is designed to prepare students majoring in other areas of business with a background of quantitative skills that facilitate the decisionmaking process. In addition to one required course, two elective courses are selected with the approval of the area advisor to complement the students major and provide the student with an appropriate background. | |||||
Required Courses Choose any three of the following (All Prerequisites must be satisfied): | |||||
| Database Management Systems | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Object-Oriented Programming II | 3 credits | |||
or
| Quantitative Methods for Accounting
Quantitative Decision Making for Business I | 3 credits
3 credits | |||
| Quantitative Decision Making for Business II | 3 credits | |||
| System Simulation | 3 credits | |||
| Bayesian Statistical Inference and Decision Making | 3 credits | |||
| Special Topics in Operations Research | 3 credits | |||
| Independent Study in Operations Research | 3 credits | |||
| Statistical Computing | 3 credits | |||
| Business Statistics II | 3 credits | |||
| Introduction to SAS Programming | 3 credits | |||
| Regression and Forecasting Models for Business Applications | 3 credits | ||||
| Advanced Data Mining | 3 credits | |||
| Independent Study in Operations Research | 3 credits | |||
The minor in statistics consists of the courses listed below.
| |||||
Choose any three of the following (All Prerequisites must be satisfied): | |||||
| Statistical Computing | 3 credits | |||
| Business Statistics II | 3 credits | |||
| Sampling Theory and Practice | 3 credits | |||
| Introduction to SAS Programming | 3 credits | |||
| Regression and Forecasting Models for Business Applications | 3 credits | ||||
| Special Topics in Applied Statistics | 3 credits | |||
| Advanced Data Mining | 3 credits | |||
| Quantitative Decision Making for Business I | 3 credits | |||
Liberal Arts Interdisciplinary Minor in Information Technology and Social Responsibility The internet age has fostered an environment of widespread interconnectedness. This hyperconnectivity, and the new media that proliferate along with it, come with their own specific problems. The purpose of this concentration is to study the effects of these new technologies on the individual, the workplace, and society at large. In this program of study students will examine the increasing importance of individual and organizational social responsibility in today’s interconnected and computer-mediated environment, as well as the specific issues that stand at the intersection of social responsibility and information technology. | |||||
Required Course: 3 credits | |||||
| Information Technology and Social Responsibility* | 3 credits | |||
Elective Courses 6 credits Two courses selected from the following: | |||||
| Mass Media and the Black American | 3 credits | |||
| Computer Ethics* (
| 3 credits | |||
| Green IT* | 3 credits | |||
| Principles of New Media* | 3 credits | |||
| Media Analysis and Criticism | 3 credits | |||
| International Communication | 3 credits | |||
| Media Ethics | 3 credits | |||
| Advanced Reporting and Writing | 3 credits | |||
| Information and Society (
| 3 credits | |||
| Mind and Computers | 3 credits | |||
| Ethics, Economics, and the Business System | 3 credits | |||
Courses may be organized into the following suggested tracks: Media | |||||
| Mass Media and the Black American | 3 credits | |||
| Principles of New Media* | 3 credits | |||
| Media Analysis and Criticism | 3 credits | |||
| International Communication | 3 credits | |||
| Media Ethics | 3 credits | |||
Information Society | |||||
| Principles of New Media* | 3 credits | |||
| International Communication | 3 credits | |||
| Advanced Reporting and Writing | 3 credits | |||
| Information and Society (
| 3 credits | |||
Philosophy and Ethics | |||||
| Computer Ethics* (
| 3 credits | |||
| Media Ethics | 3 credits | |||
| Mind and Computers | 3 credits | |||
| Ethics, Economics, and the Business System | 3 credits | |||
*For the purposes of this program, this course counts as an Arts and Sciences course.
Students in the Weissman School of Arts and Sciences or in the Marxe School of Public and International Affairs who wish to take business courses may do so by declaring a minor in statistics and quantitative modeling or in technology, business, and the Internet. Before declaring the minor, they must complete either BUS 1001 (1 credit) or have previously completed BUS 1011 (3 credits). To be awarded the minor, students must have a GPA of 2.0 or more in the courses included in the minor. Eligibility to declare such a minor is restricted to students who have an overall GPA of 2.0 or more at time they declare the minor. Courses that apply to the minor may not be used for any other requirement. This minor does not fulfill the requirement to complete a liberal arts minor. | |||||
Students must choose three courses (9 credits) from the following: Statistics and Quantitative Modeling | |||||
| Statistical Computing | 3 credits | |||
| Business Statistics II | 3 credits | |||
| Data Mining for Business Analytics | 3 credits | |||
| Introduction to SAS Programming | 3 credits | |||
| Regression and Forecasting Models for Business Applications | 3 credits | ||||
| Advanced Data Mining | 3 credits | |||
or
| Quantitative Methods for Accounting
Quantitative Decision Making for Business I | 3 credits
3 credits | |||
Technology, Business, and the Internet | |||||
| Programming and Computational Thinking | 3 credits | |||
| Object-Oriented Programming I | 3 credits | |||
| Spreadsheet Applications in Business | 3 credits | |||
| Database Management Systems | 3 credits | |||
| e-Business Technologies | 3 credits | |||
| Principles of Web Design | 3 credits | |||
| Systems Analysis and Design | 3 credits | |||
| Law and the Internet | 3 credits | |||
| Internet Marketing | 3 credits | |||
| Introduction to Information Systems and Technologies | 3 hours; 3 credits | |
| Programming and Computational Thinking | 3 hours; 3 credits | |
| Special Topics in Computer Information Systems | 3 hours; 3 credits | |
| Special Topics in Computer Information Systems | 1.5 hours; 1.5 credits | |
| Object-Oriented Programming I | 3 hours; 3 credits | |
| Object-Oriented Programming with Java | 3 hours; 3 credits | |
| Programming for Analytics | 3 hours; 3 credits | |
| Introduction to Semantic Technologies | 3 hours; 3 credits | |
| Blockchain Technologies and Applications | 3 hours; 3 credits | |
| Computer Ethics | 3 hours; 3 credits | |
| Spreadsheet Applications in Business | 3 hours; 3 credits | |
| Database Management Systems | 3 hours; 3 credits | |
| E-Business Technologies | 3 hours; 3 credits | |
| Networks and Telecommunications I | 3 hours; 3 credits | |
| Cybersecurity | 3 hours; 3 credits | |
| Principles of Web Design | 3 hours; 3 credits | |
| Green IT | 3 hours; 3 credits | |
| Foundations of Business Analytics | 3 credits | |
| Social Media Technologies in Organizations | 3 hours; 3 credits | |
| Usability, Privacy, and Security | 3 hours; 3 credits | |
| Principles of New Media | 3 hours; 3 credits | |
| Special Topics in Computer Information Systems | 3 hours; 3 credits | |
| Special Topics in Computer Information Systems | 1.5 hours; 1.5 credits | |
| Object-Oriented Programming II | 3 hours; 3 credits | |
| Web Applications Development | 3 hours; 3 credits | |
| Data Visualization | 3 hours; 3 credits | |
| Information Technology Audit | 3 hours; 3 credits | |
| Data Warehousing for Analytics | 3 hours; 3 credits | |
| Networks and Telecommunications II | 3 hours; 3 credits | |
| Ethical Hacking | 3 hours; 3 credits | ||
| FinTech: Principles and Applications | 3 hours; 3 credits | |
| Operating Systems Concepts | 3 hours; 3 credits | |
| Systems Analysis and Design | 3 hours; 3 credits | |
| Information Technology and Social Responsibility | 3 hours; 3 credits | |
| Independent Study and Research in Computer Information Systems | 3 hours; 3 credits | |
| Information Technology Development and Project Management | 3 hours; 3 credits | |
| Computer Information Systems Internship | 3 hours; 3 credits | |
| Hon Info Systems | 3 hours; 3 credits | |
| Hon Sprdsht App Bus | 3 hours; 3 credits | |
| Hon Network & Com | 3 hours; 3 credits | |
| Hon CIS I | 3 hours; 3 credits per semester | |
| Hon CIS II | 3 hours; 3 credits per semester |
| Business Statistics I | 3 hours; 3 credits | |
| Statistics for Social Science | 4 hours; 3 credits | |
| Statistical Computing | 3 hours; 3 credits | |
| Special Topics in Statistics | 3 hours; 3 credits | |
| Special Topics in Statistics | 1.5 hours; 1.5 credits | |
| Business Statistics II | 3 hours; 3 credits | |
| Sampling Theory and Practice | 3 hours; 3 credits | |
| Categorical Data Analysis | 3 hours; 3 credits | |
| Statistical Quality Control Methods | 3 hours; 3 credits | |
| Nonparametric Statistics | 3 hours; 3 credits | |
| Introduction to SAS Programming | 3 hours; 3 credits | |
| Regression and Forecasting Models for Business Applications | 3 hours; 3 credits | |
| Design and Analysis of Experimental Data | 3 hours; 3 credits | |
| Analysis of Time Series | 3 hours; 3 credits | |
| Special Topics in Applied Statistics | 3 hours; 3 credits | |
| Advanced Data Mining | 3 hours; 3 credits | |
| Independent Study and Research in Statistics | 3 hours; 3 credits | |
| Hon bus Statistics | 3 hours; 3 credits | |
| Hon Statistics I | 3 hours; 3 credits | |
| Hon Statistics II | 3 hours; 3 credits |
| Special Topics in Operations Research | 3 hours; 3 credits | |
| Special Topics in Operations Research | 1.5 hours; 1.5 credits | |
| Quantitative Methods for Accounting | 3 hours; 3 credits | |
| Quantitative Decision Making for Business I | 3 hours; 3 credits | |
| Quantitative Decision Making for Business II | 3 hours; 3 credits | |
| System Simulation | 3 hours; 3 credits | |
| Bayesian Statistical Inference and Decision Making | 3 hours; 3 credits | |
| Special Topics in Operations Research | 3 hours; 3 credits | |
| Independent Study and Research in Operations Research | 3 hours; 3 credits | |
| Hon Quant Meth Acc | 3 hours; 3 credits | |
| Hon Opr I | 3 hours; 3 credits | |
| Hon Opr II | 3 hours; 3 credits | |
| Hon Opr III | 3 hours; 3 credits |