Master of Science in Business Analytics

Master of Science: 45.0 quarter credits

About the Program

The MS in Business Analytics program is designed for students who have an interest in quantitative methods, data analysis, and using computer programs to solve business problems.

Students learn how to access and analyze data for the purpose of improved business decision-making. This program prepares students to make good business decisions with fact-based insights and an understanding of business performance from a systems view, using statistical and quantitative analysis of data as well as explanatory and predictive modeling.

The program draws upon three traditional areas of business intelligence:

  • statistics, to explore and uncover relationships in data;

  • operations research, to develop mathematical models for planning and operations; and

  • management information systems, to access and create databases that support the other two areas.

Additional Information

For additional information about the program, students should contact the Department of Decision Sciences.

Degree Requirements

Operations Research
OPR 601Managerial Decision Models and Simulation3.0
OPR 620Operations Research I3.0
Statistics
STAT 610Statistics for Business Analytics3.0
STAT 630Multivariate Analysis3.0
STAT 642Data Mining for Business Analytics3.0
Management Information Systems
MIS 612Aligning Information Systems and Business Strategies3.0
MIS 630Inter-Active Decision Support Systems **3.0
MIS 632Database Analysis and Design for Business **3.0
Capstone Project
BUSN 710Business Analytics Capstone Project3.0
Students Select One Concentration***9.0
Information Systems Concentration
Select three of the following
E-Commerce Systems I
VB.NET Programming
Predictive Business Analytics with Relational Database Data
MIS Policy and Strategy
Management of Health Care Info Systems
Information Systems Outsourcing Management
Introduction to Enterprise Application Software using SAP
Advanced Topics in Enterprise Application Software using SAP
Statistics Concentration
Select Three of the Following
Statistical Decision Theory I
Statistical Decision Theory II
Statistical Sampling
Applied Regression Analysis
Quality & Six-Sigma
Experimental Design
Advanced Statistical Quality Control
Econometrics
Time Series Econometrics
Applied Industrial Analysis
Business Conditions and Forecasting
Customer Analytics
Modeling Concentration
Select Three of the Following
Operations Research II
Advanced Mathematical Program
System Simulation
Mathematical Economics
Microeconomics
Functional Area of Business Concentration
To complete a concentration in one of these fields, the student will develop a plan of study that is mutually approved by the student and the Department Head.
Select three 600-level courses from either: ACCT, FIN, MKTG, POM or ECON
Free Electives***9.0
Select three 600-level courses within LeBow.
Total Credits45.0

*

Prerequisite is STAT 630.

**

Students will need to have the prerequisite for this course waived with permission of the instructor.

***

 Courses outside LeBow can be substituted with permission from Department Head and/or Associate Dean.

Business Statistics Courses

STAT 601 Business Statistics 3.0 Credits

This course covers the basic principles and implementation techniques of descriptive statistics, sampling, statistical inference, analysis of variance, and regression analysis. An understanding of how these tools can support managerial decision making is emphasized.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

STAT 610 Statistics for Business Analytics 3.0 Credits

This course covers the basic principles and implementation techniques of analysis of variance, simple and multiple regression analysis. An understanding of how these tools can support business analytics is emphasized. The course covers not just methods, but theory, too.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is PhD.

STAT 622 Statistical Decision Theory I 3.0 Credits

Covers philosophy and concepts of Bayesian decision techniques; diagramming decision situations; defining decision strategies; minimax, maximin, and expected value principles; measures of utility; value of additional information; optimum sample size; and analysis with discrete and continuous functions.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 624 Statistical Decision Theory II 3.0 Credits

Continues BSTAT 622. Applies principles and techniques of statistical decision theory to case problems.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 622 [Min Grade: C]

STAT 626 Statistical Sampling 3.0 Credits

Covers random processes; sampling frames; properties of estimators; simple random sampling, stratified sampling, cluster sampling, and stratified cluster sampling; ratio estimates; reliability and validity; and construction of survey instruments.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 628 Applied Regression Analysis 3.0 Credits

Covers techniques used in simple and multiple regression analysis, including residual analysis, assumption violations, variable selection techniques, correlated independent variables, qualitative independent and dependent variables, polynomial and non-linear regression, regression with time-series data and forecasting. Applications related to business decision-making will be emphasized.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-] or STAT 610 [Min Grade: B-]

STAT 630 Multivariate Analysis 3.0 Credits

An introduction to multivariate statistics that focuses on the use of statistical methods for exploring and discovering information in large business datasets. Topics will be drawn from clustering and discriminate analysis for classification, principle components analysis for data exploration and variable reduction, factor analysis for indentifying latent variables, and other traditional multivariate topics.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: C]

STAT 632 Datamining for Managers 3.0 Credits

Datamining focuses on extracting knowledge from large datasets. This course introduces the student to several key datamining concepts including classification, prediction, data reduction, model comparison and data exploration. Software and datasets are employed to illustrate the concepts.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 634 Quality & Six-Sigma 3.0 Credits

This course covers the current theory and practice in quality, with a focus on Six-Sigma Implementation. Topics will include the dynamic nature of quality, the roles of management in planning and guiding quality efforts, as well as the fundamentals of statistical methods for quality monitoring and improvement.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 636 Experimental Design 3.0 Credits

Introduces design of experiments. Covers topics including scientific approach to experimentation, completely randomized designs, randomized complete block designs, Latin square designs, factorial designs, two-factorial designs, fractional factorials, nested and split plot designs, response surfaces designs, and Taguchi methods.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 638 Advanced Statistical Quality Control 3.0 Credits

Covers advanced topics in statistical process control. Covers topics including cumulative sum (CUSUM) control charts, exponentially weighted moving average (EWMA) control charts, multivariate control charts, economic design and evaluation of control charts, performance specifications, process capability and improvement, and computer applications. Usually includes several guest speakers from service and manufacturing firms.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 634 [Min Grade: C]

STAT 642 Data Mining for Business Analytics 3.0 Credits

This course introduces students to the methods of data mining and how to apply them to business problems. Included are logistic regression, trees, neural networks, support vector machines, and marketbasket analysis. Data preparation, visualization, and feature selection also are addressed, as are boosting and random forests.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if classification is PhD and program is MS or PHD.
Prerequisites: STAT 610 [Min Grade: C]

STAT 698 Special Topics 0.5-9.0 Credits

Provides courses in topics of current interest to faculty and students. May be repeated for credit if topics vary.

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 699 Independent Study in Quantitative Methods 12.0 Credits

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 790 Seminar in Management Analysis 3.0 Credits

Provides independent research on selected management topics. Requires oral presentation and written report of graduate quality.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: C]

STAT 792 Seminar in Quality Science 3.0 Credits

Provides independent research on selected topics in quality science. Requires oral presentation and written report of graduate quality.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 601 [Min Grade: B-]

STAT 920 Stochastic Processes I 3.0 Credits

The focus of this course is on the construction of stochastic models for decision problems and the analysis of their properties. The course introduces Markov Chains and the classification of their convergence, and moves on to queuing models.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: STAT 931 [Min Grade: B-] or STAT 932 [Min Grade: B-]

STAT 922 Statistical Methods in Experimental Design 3.0 Credits

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

STAT 924 Multivariate Analysis 3.0 Credits

An introduction to multivariate statistics with topics that may include but are not limited to Matrix Algebra, the Multivariate Normal Distribution, Multivariate Analysis of Variance, Tests on Covariance Matrices, Discriminant Analysis, Multivariate Regression, Canonical Correlation, Principle Component Analysis, factor Analysis, and Cluster Analysis.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

STAT 931 Statistics for Economics 3.0 Credits

This course will cover the traditional introductory statistics topics; descriptive statistics, probability theory, random variables, discrete and continuous probability distribution, sampling distributions, estimation, and hypothesis testing. Then we’ll move on to a more advanced topic: regression analysis.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if program is PHD.

STAT 932 Statistics for Behavioral Science 3.0 Credits

This course provides a non-theoretical coverage of common statistics topics for students in the behavioral sciences. These may include, but are not limited to descriptive statistics, probability theory, random variables, discrete and continuous probability distributions, sampling distributions, estimation, hypothesis testing, analysis of variance, & regression. Emphasis is put on and examples are of behavioral topics.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Restrictions: Can enroll if program is PHD.

STAT 990 Special Topics - PhD-Quantitative Methods 0.5-9.0 Credits

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit

STAT 998 Dissertation Research in Statistics 1.0-12.0 Credit

Dissertation Research.

College/Department: LeBow College of Business
Repeat Status: Can be repeated 12 times for 24 credits

STAT 999 STAT Independent Study 3.0 Credits

STAT Independent Study.

College/Department: LeBow College of Business
Repeat Status: Can be repeated 3 times for 9 credits

Management Information Systems Courses

MIS 611 Management Information Systems 3.0 Credits

Provides students with an understanding of current information technology. Emphasizes the state and application of current technology in addressing business problems and the opportunities now and in the future, and addresses the changing role of MIS within the organizational structure.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 612 Aligning Information Systems and Business Strategies 3.0 Credits

In this course, we will examine a variety of IS issues which are important to organizations, including information systems strategy, impact of IT on organization and work processes, business process reengineering, systems architecture and project management.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 624 E-Commerce Systems I 3.0 Credits

Examines concepts of the information systems development lifecycle and methods for analyzing user information requirements. Focuses on structured techniques for designing a system, managing its development and testing, performing feasibility analyses, and ensuring both user satisfaction and achievement of functional requirements. Covers techniques such as rapid application development (RAD), prototyping, and joint analysis and design (JAD) in detail. Also covers techniques such as data flow diagramming, logical database design, and user interface design.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 630 Inter-Active Decision Support Systems 3.0 Credits

Examines the theory of DSS for use in supporting managerial decision making. Also discusses EIS, KBS, data mining, and data warehousing. Describes the benefits of online analytical processing (OLAP) to the organization and how they can be measured. Includes the development and use of DSS by student groups in a case study.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 631 VB.NET Programming 3.0 Credits

The course gives students a good understanding of the programming and system technical skills they will need to master if they plan to be MIS managers. Students will be able to write applications on a PC covering objects, controls, and database applications.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 632 Database Analysis and Design for Business 3.0 Credits

Focuses on database analysis and design for a wide range of business functions. Stresses the fundamentals of sound logical database design using techniques such as entity/relationship modeling. Examines the relational database and the object-oriented approaches to database design and handles specific design methods, such as normalization. Also discusses physical database design and data storage methodologies such as raid and hierarchical storage management (HSM). Involves a hands-on orientation with the use of tools such as oracle, Access, and Visual Basic.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 633 Predictive Business Analytics with Relational Database Data 3.0 Credits

This course introduces students to data mining through Base Programming, applied statistics, and data visualization methods in SAS. In this course, students learn to solve statistical problems rigorously and think critically with data analysis in SAS. Students acquire the analytical skills in SAS programming, capabilities in recognizing data patterns and visualizing the results.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 641 MIS Policy and Strategy 3.0 Credits

Ties together concepts from all areas of management and the economic, behavioral, functional, and technical aspects of MIS. Defines overall and context-specific information needs of organizations and focuses on the role of MIS in meeting these needs. Examines alternatives for matching MIS department structures and operations to the structures, strategies, and behaviors of organizations. Also investigates, proposes, and analyzes management policy issues relating to the management of the MIS function.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 650 Management of Health Care Info Systems 3.0 Credits

This course explores the concepts, design, and application of the management of information systems in the modern healthcare environment.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 651 Information Systems Outsourcing Management 3.0 Credits

The course presents a balances presentation of the risks and benefits of outsourcing and what should be the objectives and mindset of successful outsources. It also discusses the appropriate skill set, how to approach this risky endeavor. Although concentrating on information systems outsourcing, it lessons apply to other types of outsourcing.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 661 Introduction to Enterprise Application Software using SAP 3.0 Credits

This course introduces students to the SAP Business Suite and the fundamental concepts of enterprise application software. We will use a hands-on, case study approach to exploring SAP ERP (enterprise resource planning) capabilities such as financials, operations and human capital management.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 662 Advanced Topics in Enterprise Application Software using SAP 3.0 Credits

This course goes beyond the basics of enterprise resource planning (ERP) and explores some of the most advanced and timely topics of enterprise application software, such as analytics / business intelligence, cloud / on-demand computing, "big data" / in-memory computing and mobile applications.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: MIS 661 [Min Grade: D]

MIS 698 Special Topics in Management Information Systems 0.5-9.0 Credits

Provides courses in topics of current interest to faculty and students. May be repeated for credit if topics vary.

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit
Prerequisites: MIS 641 [Min Grade: C]

MIS 699 Independent Study 0.5-6.0 Credits

Independent Study.

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit
Prerequisites: MIS 611 [Min Grade: C] or MIS 641 [Min Grade: C] or MIS 311 [Min Grade: C] or MIS E311 [Min Grade: C] or MIS 511 [Min Grade: C]

MIS 901 Research Seminar in MIS 3.0 Credits

This course provides an introduction to research in the fields of Management Information Systems. It covers classic journal articles in the field, various research methods, and provide a perspective in a major research project during the course.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 910 Qualitative Research Methods in MIS 3.0 Credits

This course is designed as an introductory seminar on qualitative research as it is used in the fields of information systems. The course balances the acquisition of basic knowledge about the conduct of qualitative research with the application of the knowledge to research on information systems.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: MIS 901 [Min Grade: C]

MIS 920 MIS Adoption & Internalization 3.0 Credits

The objective of this course is to provide doctoral students with a solid foundation in information systems research based on readings and in the area of IS adoption and internalization. Emphasis is placed on doing exemplary research, building theory within this domain and building a career within the academic community.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: MIS 901 [Min Grade: C]

MIS 930 MIS Implementation Management 3.0 Credits

This course reviews key articles about MIS implementation management, identify key theories, appropriate research methodologies, and guide students in writing a research proposal on MIS implementation. The seminar may be a preparation for submitting the dissertation proposal.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit
Prerequisites: MIS 901 [Min Grade: C]

MIS 940 Economics of Information Technology and E-Commerce 3.0 Credits

This seminar looks at research issues in information technologies and systems through applying relevant theories and methods from economics. The topics include the impacts of IT on marketplaces and organizational structures, firm strategies in electronic commerce and the values of IT investments.

College/Department: LeBow College of Business
Repeat Status: Not repeatable for credit

MIS 990 Special Topics in PhD-Management Information Systems 0.5-9.0 Credits

College/Department: LeBow College of Business
Repeat Status: Can be repeated multiple times for credit

MIS 999 MIS Independent Study 3.0 Credits

MIS Independent Study.

College/Department: LeBow College of Business
Repeat Status: Can be repeated 3 times for 9 credits

Operations Management Courses

OPM 998 Dissertation Research in Operations Management 1.0-12.0 Credit

Dissertation Research.

College/Department: LeBow College of Business
Repeat Status: Can be repeated 12 times for 24 credits

Decision Sciences Faculty

Edward Arnheiter, PhD (University of Massachusetts, Amherst) Department of Decision Sciences. Clinical Professor. Quality implementation and management, supply chain, statistical quality control, six sigma.
Avijit Banerjee, PhD (The Ohio State University) Department of Decision Sciences. Professor. Supply chain management; operations planning and scheduling; inventory control.
Hande Yurttan Benson, PhD (Princeton University) Department of Decision Sciences. Associate Professor. Nonlinear optimization, interior-point methods.
Oben Ceryan, PhD (University of Michigan Ann Arbor) Department of Decision Sciences. Assistant Professor. Pricing revenue management; inventory control; production planning and control supply chain management.
Neil Desnoyers, MS (Drexel University) Department of Decision Sciences. Assistant Clinical Professor. Decision sciences.
Seung-Lae Kim, PhD (Penn State University) Department of Decision Sciences. Professor. Production planning and control; inventory control; Just-In-Time (JIT) and Supply Chain Management (SCM).
Benjamin Lev, PhD (Case Western Reserve University) Department Head, Department of Decision Sciences. Professor. Operations research/management science, statistics, applications, engineering management.
Merrill W. Liechty, PhD (Duke University) Department of Decision Sciences. Associate Clinical Professor. Bayesian statistics, portfolio selection, higher moment estimation.
Arunkumar Madapusi, PhD (University of North Texas Denton) Department of Decision Sciences. Assistant Clinical Professor. Manufacturing technology development; quality management; supply chain management; interface with information systems.
Hazem Diab Maragah, PhD (Louisiana University) Department of Decision Sciences. Associate Professor. Statistical quality control, total equity management, applied statistics.
Bruce D. McCullough, PhD (University of Texas) Department of Decision Sciences. Professor. Applied econometrics; reliability of statistical and econometric software; business data mining.
Thomas P. McWilliams, PhD (Stanford University) Department of Decision Sciences. Professor. Statistical quality control; sequential analysis.
Fariborz Y. Partovi, Ph.D. (The Wharton School, University of Pennsylvania) Department of Decision Sciences. Professor. The use of analytical hierarchy process and quality function deployment for strategic decisions in manufacturing and service organizations.
Wenjing Shen, PhD (University of Michigan) Department of Decision Sciences. Assistant Professor. The interface of operations management and marketing; inventory management; supply chain management.
Min Wang, PhD (Columbia University) Department of Decision Sciences. Assistant Professor.

Emeritus Faculty

Robert E. Laessig, PhD (Cornell University) Department of Decision Sciences. Professor Emeritus. Management systems integration.
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