units

FIT5097

Faculty of Information Technology

18 September 2017 22 November 2024

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This unit entry is for students who completed this unit in 2016 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

Monash University

6 points, SCA Band 2, 0.125 EFTSL

Postgraduate - Unit

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.

Faculty

Information Technology

Offered

Caulfield

  • Second semester 2016 (Evening)

Notes

Monash Online offerings are only available to students enrolled in the Graduate Diploma in Data ScienceGraduate Diploma in Data Science (http://online.monash.edu/course/graduate-diploma-data-science/?Access_Code=MON-GDDS-SEO2&utm_source=seo2&utm_medium=referral&utm_campaign=MON-GDDS-SEO2) via Monash Online.

Synopsis

This unit introduces students to the principles, techniques and applications of computer-based decision support models for business and industry. Topics include: decision trees; linear programming and optimisation; other mathematical programming methods; waiting lines and queues; time series analysis and forecasting; inventory modelling and discrete-event simulation. Models will be built and solved using spreadsheets or other computer applications as appropriate.

Outcomes

On completion of this unit, students should be able to:

  1. explain a variety of techniques for modelling business decision problems;
  2. choose the appropriate decision model for a particular problem;
  3. set up simple models and solve with hand calculations;
  4. set up mathematical models for solution in a spreadsheet or other application software;
  5. validate models and conduct a sensitivity analysis;
  6. analyse a real problem and report the results;
  7. explain the difficulty of applying models to real situations - which often requires that approximations, simplifications and generalisations be made;
  8. explain the approximate nature of some types of business modelling and why this usually means that a sensitivity analysis needs to be conducted.

Assessment

Examination (2 hours): 60%; In-semester assessment: 40%

Workload requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • Two hours of lectures
  • One 2-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 8 hours independent study per week for completing lab and project work, private study and revision.

See also Unit timetable information

Chief examiner(s)

Dr John Betts

This unit applies to the following area(s) of study

Data science

Prerequisites

At least one quantitative unit (such as Mathematics or Statistics) in an undergraduate degree.

Prohibitions

BUS5570

Additional information on this unit is available from the faculty at:

http://www.infotech.monash.edu.au/units/