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Unit of study_

ITLS6203: Analytic Methods for Logistics

Semester 1, 2022 [Normal evening] - Remote

Supply chain management, logistics, transport and infrastructure management relies on the ability to make effective decisions supported by careful and appropriate data analysis. Students undertaking this unit develop a strong understanding of the basic techniques underpinning quantitative analysis and 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, focusing on how the theories are applied in practice, drawing on real world experience in quantitative analysis. The unit covers basic statistical and data presentation techniques, spreadsheet modelling, linear optimisation methods for production and transportation applications, demand forecasting, simulation, and linear regression techniques.

Unit details and rules

Unit code ITLS6203
Academic unit Transport and Logistics Studies
Credit points 6
ITLS5200 or TPTM6495
Assumed knowledge


Available to study abroad and exchange students


Teaching staff

Coordinator Stephen Greaves,
Lecturer(s) Stephen Greaves,
Type Description Weight Due Length
Final exam (Record+) Type B final exam Final exam
Written exam
40% Formal exam period 2 hours
Outcomes assessed: LO1 LO3 LO5
In-semester test (Take-home short release) Type D in-semester exam Computer exam
In-class computer-based assessment task
30% Week 06
Due date: 29 Mar 2022 at 17:00
2 hours
Outcomes assessed: LO1 LO2 LO3
Assignment Individual Analysis and Presentation
Individual Presentation
30% Week 11 7 minute Powerpoint Presentation
Outcomes assessed: LO1 LO2 LO3 LO4 LO5
Type B final exam = Type B final exam ?
Type D in-semester exam = Type D in-semester exam ?

Assessment summary

Individual presentation: You will conduct a quantitative investigation of a real-life problem using the skills taught in this unit. You will present your work to your peers.

Computer exam (Closed Book): A 2-hour in-class computer-based assessement covering material from the first four weeks.

Final exam (Closed Book): A 2-hour comprehensive examination on theories and application covered in the unit.

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


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. 


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.


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.


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. 


0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

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:

You will lose 5% of the maximum marks for assignments for every day late. After 10 days the assignment receives a mark of 0.

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.

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.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to modelling and quantitative analysis Workshop (3 hr)  
Week 02 Presenting and Describing Data Workshop (3 hr)  
Week 03 Spreadsheet modelling Workshop (3 hr)  
Week 04 Optimisation Analysis Part I Workshop (3 hr)  
Week 05 Optimisation Analysis Part II Workshop (3 hr)  
Week 06 Mid-Term Computer-Based Assessment covering Weeks 1-5 Workshop (3 hr)  
Week 07 Probability & Modeling Uncertainty Workshop (3 hr)  
Week 08 Statistical Inference Workshop (3 hr)  
Week 09 Regression I Workshop (3 hr)  
Week 10 Regression II Workshop (3 hr)  
Week 11 Time Series Analysis & Forecasting Workshop (3 hr)  
Week 12 Simulation Modelling Workshop (3 hr)  
Week 13 Course Review, Exam Preparation Workshop (3 hr)  

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

Camm J.D., Cochran J.J., Fry M.J., Ohlmann J.W., Anderson D.R., Sweeney D.J. and William T.A. 2019, Essentials of Business Analytics Third Edition, Cengage Learning, Boston. ISBN-13:978-1-337-40642-0

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.

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

  • LO1. Select appropriate quantitatively-based analytical approaches for supporting decision-making in global logistics and transport
  • LO2. Implement these quantitative techniques in an efficient manner using computer software
  • LO3. Communicate and interpret the outputs of quantitative analysis, identifying limitations and supporting recommendations
  • LO4. Explain methods in your own words and explain how the techniques are implemented in practice in global logistics and transport
  • LO5. Recognise and address the potential shortcomings of data and analytical approaches, 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

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

No changes have been made since this unit was last offered


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