ITLS5200: Semester 1, 2020

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Units ITLS5200 Semester 1 2020 [Normal evening]

Unit of study_

ITLS5200: Quantitative Logistics and Transport

Overview

Supply chain management, as well as logistics, transport and infrastructure management, relies on the ability to make effective decisions based on the information provided by careful analysis of data. Students undertaking this unit will develop a strong understanding of the basic techniques underpinning quantitative analysis and will develop highly marketable skills in spreadsheet modelling and the communication and presentation of data to support management decision making. This unit emphasises the practical aspects of quantitative analysis with computer-based workshops. Students are guided through the basic theories used in decision making but emphasis is placed on how the theories are applied in practice, drawing on real-world experience in quantitative analysis. The unit covers demand forecasting, spreadsheet modelling, optimisation of production and transportation using linear programming, simulation and basic statistics and linear regression techniques.

Details

Academic unit	Transport and Logistics Studies
Unit code	ITLS5200
Unit name	Quantitative Logistics and Transport
Session, year ?	Semester 1, 2020
Attendance mode	Normal evening
Location	Camperdown/Darlington, Sydney
Credit points	6

Enrolment rules

Prohibitions ?	TPTM6495
Prerequisites ?	None
Corequisites ?	ITLS5000 or TPTM5001 or ITLS5100 or TPTM6241
Available to study abroad and exchange students	Yes

Teaching staff and contact details

Coordinator	Stephen Greaves, stephen.greaves@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam	Final exam Short answer and MCQ	40%	Formal exam period	2 hours
Outcomes assessed:
In-semester test	Take-home computer exam Practical exam	30%	Week 06 Due date: 16 Apr 2020 at 18:00 Closing date: 16 Apr 2020	2 hours
Outcomes assessed:
Assignment	Individual report Report	30%	Week 11 Due date: 11 May 2020 at 21:00 Closing date: 21 May 2020	5 pages
Outcomes assessed:

Take-home computer exam: The computer exam will require you to use the skills and techniques covered in the unit up to that point to solve a series of problems using Excel, and then to interpret and communicate the results. You will write up your findings in an exam booklet.
Team report: Assume you have been hired to conduct some quantitative analysis to assist a transportation/logistics company with a problem. You will be provided with a problem statement/series of questions and a data set collected by that company to assist you. You will need to use skills learned in this course to provide a short technical report summarising your analysis plus an individual reflection statement.
Final exam: The final exam will test the understanding of all the material covered in the entire unit.

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.

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.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, 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 dishonesty or plagiarism seriously.

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

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to modelling and quantitative analysis	Workshop (3 hr)
Week 02	Spreadsheet modelling	Workshop (3 hr)
Week 03	Linear programming 1	Workshop (3 hr)
Week 04	Linear programming 2	Workshop (3 hr)
Week 05	Statistical inference 1	Workshop (3 hr)
Week 06	Statistical inference 1	Workshop (3 hr)
Week 07	Computer exam workshop	Workshop (3 hr)
Week 08	Linear regression 1	Workshop (3 hr)
Week 09	Linear regression 2	Workshop (3 hr)
Week 10	Forecasting with demand modelling I	Workshop (3 hr)
Week 11	Forecasting with demand modelling 2	Workshop (3 hr)
Week 12	Simulation modelling	Workshop (3 hr)
Week 13	Final exam workshop and unit review	Workshop (3 hr)

Attendance and class requirements

Lecture recording: 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

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

Camm J. D., Cochran J. J., Fry M. J., Ohlmann J. W., Anderson D. R., Sweeney D. J. and William T. A. (2017). Essentials of Business Analytics, (2nd ed), Cengage Learning, Boston. ISBN-13: 978-1-305-62773-4.

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 the appropriate model to use in unfamiliar contexts; demonstrate an ability to implement a core set of quantitative analysis techniques in an efficient manner; and demonstrate a familiarity with a broader range of techniques
LO2. clean, chart and present data and the outputs of quantitative analysis and interpret and discuss outputs, identifying limitations and creating recommendations
LO3. explain methods in your own words and demonstrate an understanding of how the techniques are implemented in practice in the logistics, supply chain management, transport or infrastructure industries and in the broader context of decision making for business
LO4. recognise and address issues relating to the ethics of quantitative analysis and data presentation.

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

Closing the loop

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

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

Current students

Overview

Details

Enrolment rules

Teaching staff and contact details

Assessment

Assessment criteria

Late submission

Special consideration

Academic integrity

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Graduate qualities

Outcome map

Closing the loop

Additional information

Disclaimer

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