Outline

Overview

This unit of study offers a practical introduction to quantitative analysis techniques including multiple regression, uncertainty analysis, integration, structural decomposition, and dynamic systems modelling, with a strong emphasis on demonstrating their usefulness for environmental problem-solving. This unit will show students how mathematics can be brought to life when utilised in powerful applications to deal with environmental and sustainability issues. Throughout the unit of study, example applications will be explained, including climate modelling, ecosystem trophic chain analysis, linking household consumption and environmental impact, identifying socio-demographic drivers of environmental change, and the uncovering the effect of land use patterns on threats to species.

Unit details and rules

Academic unit	Physics Academic Operations
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Yinyan Liu, yinyan.liu@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Q&A following presentation, submission or placement	Assignment 2 - Q&A Q&A following presentation	10%	Multiple weeks	2~6 minutes	AI prohibited
Outcomes assessed:
Presentation	Assignment 2 - Presentation Sustainability Project Presentation	20%	Multiple weeks	Group or individual work	AI allowed
Outcomes assessed:
In-class quiz	Quiz 1 Multiple-choice quiz	2.5%	Week 04 Due date: 18 Mar 2026 at 15:00 Closing date: 18 Mar 2026	10 minutes	AI allowed
Outcomes assessed:
In-class quiz	Quiz 2 Multiple-choice quiz	2.5%	Week 06 Due date: 01 Apr 2026 at 15:00 Closing date: 01 Apr 2026	10 minutes	AI allowed
Outcomes assessed:
Written work	Assignment 1 Calculation task on sustainability issues with real-world datasets.	30%	Week 06 Due date: 02 Apr 2026 at 23:59 Closing date: 13 Apr 2026	PDF worksheet of calculation questions	AI allowed
Outcomes assessed:
In-class quiz	Quiz 3 Multiple-choice quiz	2.5%	Week 11 Due date: 13 May 2026 at 15:00 Closing date: 13 May 2026	10 minutes	AI allowed
Outcomes assessed:
In-class quiz	Quiz 4 Multiple-choice quiz	2.5%	Week 13 Due date: 27 May 2026 at 15:00 Closing date: 27 May 2026	10 minutes	AI allowed
Outcomes assessed:
Written work	Assignment 3 Submitted PDF worksheets of multiple calculation questions with written analysis (max 1200 words)	30%	Week 13 Due date: 31 May 2026 at 23:59 Closing date: 10 Jun 2026	See Canvas for more details	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Quizzes: Consisting of 4 multiple-choice questions, these quizzes will test your understanding of the material covered on relevant topics.
Assignment 1: This assignment will require you to integrate information from lectures for quantitative analysis of real-world issues.
Assignment 2: This assignment will require you to apply techniques from lectures to sustainable issues
Assignment 3: This assignment will require you to integrate information from lectures to create a concise written argument.

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.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

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.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	The (absolute) basis of statistics	Lecture (2.5 hr)
Week 02	Hypothesis testing I	Lecture (2.5 hr)
Week 03	Hypothesis testing II	Lecture (2.5 hr)
Week 04	Multivariate regression	Lecture (2.5 hr)
Week 05	Multivariate regression II	Lecture (2.5 hr)
Week 06	Regression applications	Lecture (2.5 hr)
Week 07	Error propagation and decision making under uncertainty	Lecture (2.5 hr)
Week 08	Integration	Lecture (2.5 hr)
Week 09	Integration applications	Lecture (2.5 hr)
Week 10	Structural decomposition analysis	Lecture (2.5 hr)
Week 11	SDA applications and structural path analysis	Lecture (2.5 hr)
Week 12	SPA applications	Lecture (2.5 hr)
Week 13	Advancing Sustainability Thinking & Course Review	Lecture (2.5 hr)

Attendance and class requirements

As of semester 2, 2023, the main delivery method for this unit is in-class again.

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.

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. be aware of the importance of calculations and techniques for sustainability issues
LO2. understand the principles of common analytical techniques
LO3. apply the techniques to practical sustainability issues, particularly with real-world data
LO4. make connections between techniques, results, data, meanings and qualitative analysis
LO5. have developed a “tool box” of analytical skills for assessing sustainability issues
LO6. have demonstrated critical thinking and practical skills in the tutorials
LO7. Present quantitative insights on sustainability issues effectively, both orally and in writing.

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 to the lecture structure compared to previous semesters.

Additional information

Equity Access and Diversity Statement in Unit Outlines

The School of Physics recognises that biases and discrimination, including but not limited to those based on gender, race, sexual orientation, gender identity, religion and age, continue to impact parts of our community disproportionately. Consequently, the School is strongly committed to taking effective steps to make our environment supportive and inclusive and one that provides equity of access and opportunity for everyone.

The School has three Equity Officers as a point of contact for students and staff who may have a query or concern about any issues relating to equity, access and diversity. If you feel you have been treated unfairly, bullied, discriminated against or disadvantaged in any way, you are encouraged to talk to one of the Equity Officers or any member of the Physics staff.

More information can be found at

https://sydney.edu.au/science/schools/school-of-physics/equity-access-diversity.html

Any student who feels they may need a special accommodation based on the impact of a disability should contact Disability Services:

http://sydney.edu.au/current_students/disability/ who can help arrange support.

Science student portal

Work, health and safety

We are governed by the Work Health and Safety Act 2011, Work Health and Safety Regulation 2011 and Codes of Practice. Penalties for non-compliance have increased. Everyone has a responsibility for health and safety at work. The University’s Work Health and Safety policy explains the responsibilities and expectations of workers and others, and the procedures for managing WHS risks associated with University activities.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links

PHYS5032: Techniques for Sustainability Analysis

Semester 1, 2026 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Work, health and safety

Disclaimer

On this page

Useful links