澳门六合彩历史记录

Graduate Studies

Business Analytics
2024-2025

Director: Jessica Lin
Graduate Committee Chairperson: Anna Valeva
Graduate Advisor: Anna Valeva
Office: Stipes Hall 431
Telephone: (309) 298-1152
E-mail: afed@wiu.edu
Website: wiu.edu/afed
Location of Program Offering: Macomb, Online

Learning Outcomes

For student learning outcomes, please see wiu.edu/provost/learningoutcomes.

Program Description

The School of Accounting, Finance, 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 Quantitative 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

  • Non-degree students must meet the admission requirements for the Graduate School.
  • Degree students must meet the admission requirements for their degree program.
  • Must have completed at least one course in introductory statistics equivalent to Stat 171 or higher with a course in calculus (equivalent to Math 137) and/or a course in linear Algebra desirable, but 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 (罢翱贰贵尝庐). Students must meet institutionally mandated minimum 罢翱贰贵尝庐 scores.

Certificate Requirements

I. Core Courses: 15 s.h.

DS 421G Data Visualization for Decision Making (3)
or
DS 521 Advanced Data Visualization (3)

DS 435G Applied Data Mining for Business Decision Making (3)
or
DS 535 Advanced Data Mining for Business Analytics (3)

DS 480G Predictive Analytics (3)
or
DS 580 Advanced Predictive Analytics and Times Series Forecasting (3)

DS 490G Statistical Software for Data Management and Decision Making (3)
or
DS 504 R Software for Data Management and Decision Making (3)

DS 500 Introduction to Business Analytics (3)

II. Integrative Experience: 3 s.h.

DS 603 Business Analytics Assessment (0)
and

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

or

Integrative Experience in Business Analytics:
ACCT 551 Accounting Analytics (3)
CS 433G Python for Data Explorations (3)
CS 481G Database Programming (3)
DS 501 Independent Research (3)
*DS 521 Advanced Data Visualization (3)
DS 523 Advanced Management Science Techniques & Analytics (3)
*DS 580 Advanced Predictive Analytics and Times Series Forecasting (3)
DS 589 Seminar in Contextual Business Analytics (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 school

TOTAL: 18 s.h.

*If not used as a core course.

Course Descriptions

Accounting (ACCT)

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

Computer Science (CS)

433G Python for Data Explorations. (3) Programming data-intensive and computational applications in Python. The emphasis is on using Python鈥檚 various technical libraries and tools geared toward data manipulation, visualization, and analysis, as well as scientific computing. Relevant case studies are used to hone these skills. Not open to MS in Computer Science students. Prerequisites: (CS 114 or CS 214) and (MATH 128 or STAT 171).

481G Database Programming. (3) Introduction to practical aspects of querying relational databases (using SQL). Creating applications written in high-level, general-purpose programming languages (Python) for interacting with databases. Necessary programming fundamentals, principles of database querying, developing applications that work with databases. Prerequisites: STAT 171 or permission of the instructor.

Decision Sciences (DS)

421G Data Visualization for Decision Making. (3) This course provides introduction to 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. Not open to students who have already completed DS 521. Prerequisites: STAT 171 or DS 200 or equivalent or consent of instructor.

423G Management Science Techniques & Business Analytics. (3) An introduction to management science/operations research techniques. Students are introduced to the theory and applications of linear, integer, goal, and dynamic programming models; transportation, assignment, network and inventory models; PERT/CPM, capital budgeting, and decision theory. Not open to students who have already completed DS 523.Prerequisites: STAT 171 or equivalent.

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: DS 303 or STAT 276 or permission of instructor.

480G Predictive Analytics. (3) A survey of topics in predictive analytics methods and techniques essential for business analysts. Topics include time series regression, logistic regression, neural networks, decision trees, ensemble models, and simulation models for understanding the effect of uncertainty. Not open to students who have already completed DS 580. Prerequisites: DS 490 or CS 114, and 6 s.h. of either STAT or DS coursework; or permission of the instructor.

489G Seminar in Contextual Business Analytics. (3) An industry, case study, focused course that explores topics relevant to applying business analytics models and theories to current corporate projects. Exact topics will change based on instructor expertise and market trends. Prerequisites: DS 490 or CS 114, and 6 s.h. of additional DS coursework; or permission of the instructor.

490G Statistical Software for Data Management and Decision鈥揗aking. (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. Prerequisites: STAT 171 or equivalent, and DS 303 or PSY 223 or SOC 324 or POLS 284 or equivalent; or permission of the instructor.

500 Introduction to Business Analytics. (3) 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.

501 Independent Research. (1鈥�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.

504 R Software for Data Management and Decision Making. (3) This course provides students with the concepts of statistical computing. Students will gain experience with R and its application. R programming skills will be introduced thoroughly, and data preparation and visualization using R will be covered. Prerequisite: STAT 171.

521 Advanced Data Visualization. (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 421G, or permission of the instructor.

523 Advanced Management Science Techniques & Analytics. (3) Applications of management science tools and techniques for effective decision making with emphasis on model building. Topics include linear, integer, nonlinear, and dynamic programming, sensitivity analysis, and simulation. Prerequisite: DS 423G, or permission of the instructor.

535 Data Mining for Business Analytics. (3) An in-depth examination of data mining methods and techniques for business analytics. Students will develop techniques for data preparation, retrieval, modeling, and analytics aimed at the production of decision rules for specific business goals. Credit cannot be earned for both DS 435G and DS 535. Prerequisites: DS 504 or permission of the instructor.

580 Advanced Predictive Analytics and Times 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 480G, or permission of the instructor.

589 Seminar in Contextual Business Analytics. (3) An industry, case study, focused course that explores topics relevant to applying business analytics models and theories to current corporate projects. Exact topics will change based on instructor expertise and market trends. Students cannot earn credit for both DS 489G and DS 589. Prerequisites: DS 490 or CS 114, or DS 504; and 6 s.h. of additional DS coursework; or permission of the instructor.

599 Decision Sciences Internship. (1鈥�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.

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. Prerequisite: Enrollment in the Post-Baccalaureate Certificate in Business Analytics.

Economics (ECON)

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

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 581 and ECON 506; or permission of the graduate advisor.

599 Internship. (1鈥�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.

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

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.

Mathematics (MATH)

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.