Graduate Studies

Business Analytics
2017-2018

Gainful Employment Information

Chairperson: Tej Kaul
Graduate Committee Chairperson: Steven Rock
Office: Stipes Hall 430
Telephone: (309) 298-1153 Fax: (309) 298-1020
E-mail: Economics@wiu.edu
Website: wiu.edu/eds
Location of Program Offering: Macomb, Quad Cities

Program Description

The Department of Economics and Decision Sciences offers a post-baccalaureate certificate program to graduate level students who are interested in the field of Business Analytics. This program brings together the technical skills of data mining, statistical modeling, and forecasting for data driven decision making and for solving the analytical problems of the contemporary business world. The program is designed for graduate level students in diverse backgrounds. Graduates from undergraduate programs in quantitative and biological sciences, economics, sociology, psychology, business, computer sciences, physics, mathematics, actuarial science, engineering, or education, as well as working professionals desiring to sharpen their data-analysis and business analytical skills and/or learn advanced statistical methods will especially benefit from the high-demand post-baccalaureate certificate program in business analytics.

The Business Analytics post-baccalaureate certificate program is closely related to the Master's degree programs in Economics, Applied Statistics and Decision Analytics, Business Administration or Mathematics. Students interested in pursuing one of these degree programs may apply some semester hours earned in the Business Analytics certificate towards the fulfillment of requirements of these or other graduate programs. See respective graduate advisors for more information about these graduate programs.

Requirements for Enrollment

Students who want the post-baccalaureate certificate must meet admission requirements. Non-degree students must meet the admission requirements for the Graduate School; degree students must meet the admission requirements for their degree program. The post-baccalaureate certificate program in business analytics students must hold an earned baccalaureate degree from an accredited institution. Applicants are expected to have had at least one course in introductory statistics equivalent to Stat 171 or higher. A course in calculus (equivalent to Math 137) and/or a course in linear Algebra would be desirable but is not required to fulfill the deficiencies. Students deficient in the above minimum requirements may be required to complete deficiencies before starting the post-baccalaureate certificate program in business analytics. Students whose native language is other than English must demonstrate written and spoken English language proficiency. Evaluation of English language proficiency will be based on the student's scores on the Test of English as a Foreign Language (TOEFL®). Students must meet institutionally mandated minimum TOEFL® scores as established by the WIU Center for International Studies. All potential students must file an official application to the WIU School of Graduate Studies and/or the WIU Center for International Studies.

Certificate Requirements

I. Business Background: 1 s.h.

DS 500 Introduction to Business Analytics (1)

II. Core Courses: 11 s.h.

DS 435G Applied Data Mining for Business Decision Making (3)
or
DS 535 Advanced Data Mining for Business (3)
DS 490G Statistical Software for Data Management and Decision Making (3)
DS 521 Data Visualization (2)
DS 580 Business Analytics and Forecasting (3)

III. Directed Elective (select one from the following list): 3 s.h.

ACCT 445G Analysis and Use of Financial Statements (3)
ACCT 540 Contemporary Issues in Accounting (3)
ACCT 547 Corporate Financial Reporting and Analysis (3)
ACCT 580 Advanced Auditing (3)
CS 460G Artificial Intelligence Methods (3)
CS 465G Computer Graphics (3)
CS 470G Database Systems (3)
CS 500 Intensive Programming Review (3)
DS 523 Management Science Techniques and Business Analytics (3)
DS 533 Applied Business Forecasting and Planning (3)
DS 540 Applied Stochastic Models for Business Analytics (3)
ECON 481G Mathematical Economics (3)
ECON 503 Applied Price Theory (3)
ECON 504 Price Theory (3)
ECON 506 Econometrics I (3)
FIN 555 Investment Management (3)
FIN 565 Financial Management: Theory and Practice (3)
IS 405G Business Intelligence and Decision Support Systems (3)
MATH 552 Scientific Computing (3)
STAT 553 Applied Statistical Methods (3)

IV. Capstone Experience: 3 s.h.

Internship in Business Analytics:
CS 595 Graduate Computer Science Internship (3)
DS 620 Decision Sciences Internship (3)
ECON 599 Internship (3)
MATH 602 Internship in Applied Mathematics (3)

or

Supervised Project in Business Analytics:
ACCT 551 Advanced Management Accounting/Systems (3)
DS 600 Independent Research (3)
ECON 501 Readings in Economics (3)
ECON 507 Econometrics II (3)
FIN 496G Futures and Options Markets (3)
MATH 596 Project in Applied Mathematics (3)
MATH 601 Advanced Project in Applied Mathematics (3)
or other course numbers as recommended by the department

TOTAL: 18 s.h.

Course Descriptions

Accounting (ACCT)

445G The Analysis and Use of Financial Statements. (3) Integration of concepts from accounting, economics, business strategy, and other business disciplines to analyze financial statements for investment and credit decision making.  Prerequisite: ACCT 342 with a grade of C or better, or permission of the instructor.

540 Contemporary Issues in Accounting. (3) A conceptual study of financial accounting and reporting topics with an emphasis on current regulatory and policy issues. Emphasis will be placed on critical thinking, written and oral communication skills, and professional development. Prerequisite: ACCT 342 or equivalent with a grade of C or better.

547 Corporate Financial Reporting and Analysis. (3) An analysis of corporate financial reports and other disclosures, with emphasis on how this information can be used for making investment and credit decisions. This course will also consider the impact of accounting choice decisions on financial reporting and analysis.Not open to undergraduate or graduate accountancy students.  Prerequisite: ACCT 307 or equivalent.

551 Advanced Management Accounting/Systems. (3) Application of managerial accounting concepts and techniques to develop, analyze, and interpret information and participate in management decision making processes. Prerequisite: ACCT 451 or equivalent with a grade of C or better.

580 Advanced Auditing. (3) Advanced auditing functions, techniques, and guidance within internal (operational), regulatory and governmental auditing as independent, but related, fields of study. The course will also cover advanced topics and/or methods of fraud examination, as well as current research in the field. Prerequisite: ACCT 480 or equivalent with a grade of C or better.
Computer Science (CS)

460G Artificial Intelligence Methods. (3) An introduction to the main principles and methods of artificial intelligence. Solving problems by searching, knowledge and reasoning; machine learning; current AI applications. Programming paradigms relevant to AI will be explored. Graduate students will need to write a term paper on a topic in or related to AI. Prerequisite: CS 351.

465G Computer Graphics. (3) Introduction to computer-generation of graphs and pictures, using both character and pixel graphics methods, in two and three dimensions. Animation techniques, CAD methods. Computer lab projects. Prerequisite: CS 351 or equivalent.

470G Database Systems. (3) Survey of data models with emphasis on the relational model. Data normalization. Query languages and query optimization. Design and security considerations. Exposure to commercial database management systems. Prerequisite: CS 351 or NET 432. Credit cannot be given for both CS 470, and CS 483 or IS 342.

500 Intensive Programming Review. (3) This course will review computer programming, object-oriented design, linear and non-linear data structures, and the software development lifecycle. All concepts will be reinforced through hands-on programming assignments and projects. Prerequisite: CS 350.

595 Graduate Computer Science Internship. (3) A one-semester on-the-job experience in an industrial facility or research laboratory. Graded S/U. Must have completed at least 9 hours of Computer Science graduate coursework and department permission required.
Decision Sciences (DS)

435G Applied Data Mining for Business Decision Making. (3) This course provides an introduction to data mining methods for business applications. Students will learn the basics of data selection, preparation, statistical modeling and analysis aimed at the identification of knowledge fulfilling organizational objectives. Prerequisite: STAT 171 or equivalent or permission of instructor.

490G Statistical Software for Data Management and Decision Making. (3, repeatable to 6 for different titles) This course provides students with the basic concepts of statistical computing. Students will gain experience with statistical software packages, such as SAS or SPSS, and their applications. Methods of data preparation and validation, analysis, and reporting will be covered. Prerequisite: STAT 171 or equivalent, or PSY 223, or SOC 232, or POLS 284, or permission of department chairperson.

500 Introduction to Business Analytics. (1) Business analytics generally refer to the use of statistical and quantitative analysis for data-driven decision-making. This course introduces students to the foundations of business analytics problems and applications. Lectures will be supplemented with current business world examples. Prerequisite: Graduate standing.

521 Data Visualization. (2–3) This course focuses on the process and methods of visualizing information for the purpose of communicating actionable findings in a decision-making context. Hands-on experience with software for sourcing, organizing, analyzing, comprehending, reducing and visualizing data, resulting in a clear message. Prerequisites: DS 303 or equivalent, or permission of the instructor.

523 Management Science Techniques and Business Analytics. (3) Applications of management science tools and techniques for effective decision making with emphasis on model building. Topics include PERT/CPM, transportation models, linear, goal, integer and dynamic programming, and queuing theory. Prerequisite: DS 503.

533 Applied Business Forecasting and Planning. (3) A survey of the basic forecasting methods and techniques essential for modern managers. Topics include moving average and decomposition techniques, ARIMA processes, regression techniques, and technological methods such as Delphi and S-curves. Prerequisite: DS 503 or STAT 171 or equivalent.

535 Advanced Data Mining for Business. (3) This course furthers the study of data mining methods and techniques for business applications. Students will develop more advanced techniques for data preparation, information retrieval, statistical modeling and analysis aimed at the production of decision rules for specific business goals. Prerequisites: DS 435G or permission of the instructor.

540 Applied Stochastic Models in Business Analytics. (3) This course introduces stochastic models for studying phenomena in management science, operations research, finance, actuarial science, and engineering. Heuristic minded approach aimed at developing “probabilistic thinking” is taken in the treatment of probability concepts, stochastic processes, model simulation, and applications. Prerequisite: DS 303 or equivalent, or permission of the instructor.

580 Predictive Analytics and Time-Series Forecasting. (3) This course introduces analytical models and tools used for continuous iterative exploration and investigation of past business performance to gain insight and drive decision. Predictive modeling, forecasting, and design of experiments will be covered. Prerequisites: DS 303 or equivalent, or permission of the instructor.

600 Independent Research. (1–3, repeatable twice up to a maximum of 6) Independent research and study of selected topics in decision sciences. Prerequisites: Completion of six graduate hours in decision sciences and permission of the Department Chairperson.

602 Department Research Seminar. (0) A survey of contemporary theoretical and applied economic research. Graded S/U. Prerequisite: Graduate standing.

603 Comprehensive Examination. (0) All majors are required to satisfactorily complete the knowledge assessment examination prior to graduation.  Graded S/U. Prerequisite: Economics major.

604 Applied Statistics and Decision Analytics Assessment. (0) All students in the Applied Statistics and Decision Analytics program are required to satisfactorily complete the assessment examination prior to graduation. This course also offers career preparation guidance and therefore should be taken during the student’s last semester on campus. Prerequisite: Enrollment in the Applied Statistics and Decision Analytics program.

603 Business Analytics Assessment. (0) All students in the post-baccalaureate certificate in business analytics are required to satisfactorily complete the assessment examination prior to graduation. This course also offers career preparation guidance and therefore should be taken during the student’s last semester on campus. Prerequisite: Enrollment in the Post-Baccalaureate Certificate in Business Analytics.

620 Decision Sciences Internship. (1–6, not repeatable) Integrates decision sciences theories with application to actual business practices. Students are exposed to a variety of positions within the business firm during the semester. All internships are supervised by a faculty coordinator and an executive in the business firm. Analytic reports of work accomplished by each student are presented to the coordinator. Graded S/U only. Prerequisites: Completion of six hours of decision sciences courses and written permission of the Department Chairperson.

Economics (ECON)

481G Mathematical Economics. (3) Introduction to the mathematics most frequently used by economists-basic set theory; linear algebra; differentiation; comparative statistics; optimization; constrained optimization; linear programming. Prerequisites: ECON 381(Grade of C or better) or passing department placement exam.

501 Readings in Economics. (1–3, repeatable to 3) Graded S/U. Prerequisites: Permission of Department Graduate Committee Chairperson.

503 Applied Price Theory. (3) Application of economic theory and methods to managerial decision making. Topics include demand, cost and production analysis and estimation; forecasting; pricing policy; risk and uncertainty problems; and capital budgeting. Prerequisite: ECON 509 or equivalent.

504 Price Theory. (3) An analysis of consumer and firm behavior, market and multimarket equilibrium, and welfare economics. Prerequisite: ECON 481G or permission of the graduate advisor and ECON 509 or equivalent.

506 Econometrics I. (3) Elements of the theory and practice of econometrics: including univariate and multivariate single equation models, statistical problems such as multicollinearity, special techniques and applications, and an introduction to simultaneous equations models.  Students will complete a project involving hypothesis formulation, data collection, analysis using statistical software, and written presentation of results. Prerequisite: ECON 509 or equivalent.

507 Econometrics II. (3) Advanced econometric estimation to include estimating micro and macroeconomic functions through simultaneous equation systems, dummy dependent variable models; and multivariate analysis. Class culminates in an independent research project.  Prerequisites: ECON 481G or permission of the graduate advisor, and ECON 506.

599 Internship. (1–12, repeatable to 12 hours) Only three hours per semester can be included in the degree plan. With prior approval of the graduate advisor, up to six hours can be included in the degree plan for internships covering the entire academic year. Graded S/U. Prerequisites: Graduate standing and permission of departmental graduate advisor.

Finance (FIN)

496G Futures Options and Options Markets. (3) The course presents a foundation in futures and options contracts examining the types of contracts, structure of the markets, pricing of contracts, and applications in risk management. Prerequisites: FIN 311 or 331 or equivalent, or permission of the instructor.

555 Investment Management. (3) An introductory course in investment management designed to provide the conceptual basis for investment decision making. Topics will include how the security markets work, techniques of security analysis, valuation theory, and introduction to modern portfolio theory.

565 Financial Management: Theory and Practice. (3) An advanced course in corporate financial management intended to provide a conceptual framework for analyzing the major types of decisions made by financial executives. Topics dealing with the acquisition and administration of corporate capital will be discussed in an applied setting stressing their relevance to practical problems in financial management. Case studies and team written reports are used to provide students with an opportunity to apply known concepts and principles to realistic situations. Prerequisite: FIN 331 or equivalent.

Information Systems (IS)

405G Business Intelligence and Decision Support Systems. (3) This course focuses on the features, uses, and design strategies for IT-enabled managerial decision support. Data-oriented techniques for business intelligence and corporate decision making are emphasized. Prerequisites: IS 340 and, DS 303 or STAT 276, or permission of school director.

Mathematics (MATH)

552 Scientific Computing. (3) Design, analysis, and MATLAB  or Mathematica implementation of algorithms for solving problems of continuous mathematics involving linear and nonlinear systems of equations, interpolation and approximation, numerical differentiation and integration, and ordinary differential equations with a significant lean toward applications. Prerequisites: MATH 311 and MATH 333, or equivalents.

596 Project in Applied Mathematics. (3, repeatable to 6) A project in applied mathematics or statistics, or with a professional institution, which will be presented in a final paper or portfolio, demonstrating entry into an applied mathematics field. Graded S/U. Prerequisite: Permission of the Graduate Committee.

601 Advanced Project in Applied Mathematics. (3, repeatable to 6) Project in an advanced topic of mathematics or statistics, which will be presented in a final paper or portfolio, demonstrating advanced proficiency in an applied mathematics field. Graded S/U. Prerequisite: Permission of the Graduate Committee.

602 Internship in Applied Mathematics. (3, repeatable to 6) Mathematical work or training conducted at a professional institution, university or government organization, which will be presented in a final paper or portfolio, demonstrating advanced proficiency in an applied mathematics field. Graded S/U. Prerequisite: Permission of the Graduate Committee.
Statistics (STAT)

553 Applied Statistical Methods. (3) Introduction to probability and statistics with a significant lean toward applications. Topics include probability, probability distributions, Central Limit Theorem, sampling distributions (t, F, Chi-Square), parameter estimation, hypothesis testing, nonparametric statistics, ANOVA, and linear regression. Prerequisites: MATH 231 and STAT 276, or equivalents.