Graduate Studies

Business Analytics 2014-2015

Chairperson: Tej Kaul
Graduate Committee Chairperson: Steven Rock
Office: Stipes Hall 430
Telephone: (309) 298-1153 Fax: (309) 298-1020
Location of Program Offering: Macomb

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)
DS 490G Statistical Software for Data Management and Decision Making (3)
DS 540 Applied Stochastic Models for Business Analytics (2)
DS 580 Business Analytics and Forecasting (3)

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

CS 500 Intensive Programming Review (3)
DS 475G Bayesian Quantitative Applications (3)
DS 523 Management Science Techniques and Business Analytics (3)
ECON 481G Mathematical Economics (3)
ECON 503 Applied Price Theory (3)
ECON 506 Econometrics I (3)
MATH 552 Scientific Computing (3)
STAT 553 Applied Statistical Methods (3)

IV. Capstone Experience: 3 s.h.

Internship in Business Analytics (3)
Supervised Project in Business Analytics (3)

(DS 600, DS 620, ECON 501, ECON 599, or other course numbers as recommended by the department)

TOTAL: 18 s.h.

Course Descriptions

Computer Science (CS)

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.

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.

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.

540 Applied Stochastic Models in Business Analytics. (2) 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 Business Analytics and 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) 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.

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.

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.

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.

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.

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.