Outline

Overview

The ability to understand and mathematically formulate decision problems is a fundamental skill for managers in any organisation. This unit focuses on basic management science modelling techniques used in capacity planning, production management, and resource allocation. Students learn to approach complex real-life problems, formulate appropriate models and offer solution procedures to ensure optimal use of resources. Methods include linear programming, integer programming, quadratic programming, and dynamic programming.

Unit details and rules

Unit code	QBUS2310
Academic unit	Business Analytics
Credit points	6
Prohibitions ?	ECMT2620
Prerequisites ?	Students commencing from 2018: QBUS1040; Pre-2018 commencing students: BUSS1020 or DATA1001 or ECMT1010 or ENVX1001 or ENVX1002 or STAT1021 or ((MATH1005 or MATH1015) and MATH1115) or 6 credit points of MATH units which must include MATH1905.
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Simon Loria, simon.loria@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam	Final exam Written exam	50%	Formal exam period	2 hours
Outcomes assessed:
Online task	Homework Task 1 Complete simple LP formulation task and upload to Canvas using Turnitin	2.5%	Week 06 Due date: 30 Mar 2020 at 18:00 Closing date: 30 Mar 2020	30 minutes
Outcomes assessed:
Online task	Homework Task 2 Complete sensitivity analysis task and upload to Canvas using Turnitin	2.5%	Week 06 Due date: 03 Apr 2020 at 18:00 Closing date: 03 Apr 2020	30 minutes
Outcomes assessed:
In-semester test	Mid-semester exam Written exam	25%	Week 07 Due date: 08 Apr 2020 at 16:15 Closing date: 08 Apr 2020	n/a
Outcomes assessed:
Assignment	Individual Assignment Practical assessment	20%	Week 12 Due date: 18 May 2020 at 23:59 Closing date: 28 May 2020	n/a
Outcomes assessed:

Assessment summary

Individual assignment: Students will be required to model real-life business problems/cases. They will also be required to solve the model using computer software and provide managerial insights and recommendations.
Homework tasks 1 and 2: These two simple tasks are designed primarily to allow students to practice the process scanning their handwritten work and uploading this work to Canvas using Turnitin in preparation for both the mid semester and final exams which will require students to follow the same time constrained upload process.
Mid-semester exam: This open book exam will examine all unit content from weeks 1-6 inclusive. There will be no programming required nor will there be any reading time. All answers are to be handwritten on paper, scanned and saved as a pdf file and then uploaded to Canvas using Turnitin all within the time allowed for the exam. The exam itself it will test student understanding of theory and the ability to solve problems. It will not include a programming component, but students may be asked to interpret computer output and partial models which will be provided. Students will be required to demonstrate an understanding of the theoretical principles and application of the models covered in the unit.
Final exam: This open book exam will examine all unit content from weeks 1-13 inclusive. There will be no programming component nor will there be any reading time. All answers are to be handwritten on paper, scanned and saved as a pdf file and then uploaded to Canvas using Turnitin all within the time allowed for the exam. Students will be required to demonstrate an understanding of the theoretical principles and application of the models covered in the unit. They may also be asked to interpret computer outputs and partial models which will be provided.

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

All assignments submitted after the due date will be penalised at the rate of 5% per day.

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Management science: introduction	Lecture and tutorial (4 hr)
Week 02	Linear programming: model formulation and graphical solution	Lecture and tutorial (4 hr)
Week 03	Linear programming: computer solution and sensitivity analysis	Lecture and tutorial (4 hr)
Week 04	Linear programming: modelling examples	Lecture and tutorial (4 hr)
Week 05	Integer programming	Lecture and tutorial (4 hr)
Week 06	1. Transportation; 2. Transshipment; 3. Assignment problems	Lecture and tutorial (4 hr)
Week 08	Network flow models	Lecture and tutorial (4 hr)
Week 09	Project management	Lecture and tutorial (4 hr)
Week 10	Non-linear programming	Lecture and tutorial (4 hr)
Week 11	Queuing analysis	Lecture and tutorial (4 hr)
Week 12	Simulation	Lecture and tutorial (4 hr)
Week 13	Revision	Lecture and tutorial (4 hr)

Attendance and class requirements

Lecture recordings: All lectures and seminars are recorded and will be available on Canvas for student use. Please note the Business School does not own the system and cannot guarantee that the system will operate or that every class will be recorded. Students should ensure they attend and participate in all classes.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Introduction to Management Science: Global Edition, 11/E or later by Bernard Taylor.

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. select between basic models of management science according to the business context
LO2. create models for management decision making
LO3. identify the potential limitations of the models and suggest creative solutions to overcome model weaknesses
LO4. make decisions based on the output of the management science model
LO5. use special software tools for solving and analysing management science models.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Additional information

More information can be found on Canvas.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

QBUS2310: Management Science

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect