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Graduate Course Proposal Form Submission Detail - QMB6303
Tracking Number - 2998

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Current Status: Approved by SCNS - 2013-01-25
Campus: Sarasota
Submission Type: New
Course Change Information (for course changes only):
Comments: USF-SM approved 10/30/12. to Sys 12/6/12. Issues of concurrence. ISSUES Resolved. SCNS approved effective 3/1/13. Nmbr 6315 Approvd 6303

Detail Information

  1. Date & Time Submitted: 2012-11-13
  2. Department: Information Systems and Decision Sciences
  3. College: BM
  4. Budget Account Number: 140700004
  5. Contact Person: Dr. Anurag Agarwal
  6. Phone: 9413594522
  7. Email:
  8. Prefix: QMB
  9. Number: 6303
  10. Full Title: Applied Business Analytics
  11. Credit Hours: 3
  12. Section Type: C - Class Lecture (Primarily)
  13. Is the course title variable?: N
  14. Is a permit required for registration?: N
  15. Are the credit hours variable?: N
  16. Is this course repeatable?:
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum): Appl. Bus. Analytics
  19. Course Online?: B - Face-to-face and online (separate sections)
  20. Percentage Online: 0
  21. Grading Option: R - Regular
  22. Prerequisites: None
  23. Corequisites: None
  24. Course Description: This course covers a variety of tools and techniques for the analysis of large and complex business data and how to apply them to various business problems ranging from manufacturing, marketing, finance, accounting, economics and management.

  25. Please briefly explain why it is necessary and/or desirable to add this course: Needed for program/concentration/certificate change
  26. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? The demand of this course is determined by the demand for the certificate program in Business Analytics. Many universities are offering new programs in Business Analytics because of the demand for such programs, which in turn is driven by the demand in the job market for skills in Business Analytics.
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? No
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) None besides having a terminal degree in the discipline
  29. Objectives: Students will learn:

    -How to develop skills in compiling data from heterogeneous sources

    - How to develop skills in defining business problems as an analytics problem

    - How to identify the right analysis tool for a given problem

    - A better knowledge of the various data mining methods

    - A better knowledge of the various multivariate statistical techniques

  30. Learning Outcomes: Students will demonstrate:

    - An understanding and familiarity of many data mining and multivariate data analysis techniques

    - The ability to solve business problems requiring data analysis, using the most appropriate analytics approach

  31. Major Topics: - Heterogeneous data sources

    - Multi-variate analyses

    - Multiple regression analysis

    - Design of Experiments

    - Data Mining techniques

  32. Textbooks: E. Turban, R. Sharda, J. Aronson, and D. King, Business Intelligence: A Managerial Approach, Pearson Prentice Hall, 2008, ISBN-13: 978-0-13-234761-7.

    R. Mosimann, P. Mosimann, and M. Dussault, The Performance Manager: Proven Strategies for Turning Information into Higher Business Performance, Cognos Press, 2007, ISBN 978-0-9730124-1-5.

  33. Course Readings, Online Resources, and Other Purchases: At the discretion of the instructor, current readings will be assigned.
  34. Student Expectations/Requirements and Grading Policy: Participation in Discussions 25%

    Homework Assignments 25%

    Exam-1 (1st half of material) 25%

    Exam 2 (2nd half of material) 25%

  35. Assignments, Exams and Tests: There will be assignments worth 25% of the grade and two exams worth 50% of the grade.
  36. Attendance Policy: Course Attendance at First Class Meeting – Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation – Registration - 4.0101,

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. It’s the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

  37. Policy on Make-up Work: Under extreme medical circumstances and with documentation from the doctor’s office, missed exams may be made up if feasible and at the discretion of the instructor.
  38. Program This Course Supports: Certificate program in “Business Analytics”
  39. Course Concurrence Information: This course may be taken as an elective in the certificate program in Lean Operations and Six Sigma

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