ECON2209 Business Forecasting

Subject Code

ECON2209

Study Level

Undergraduate

Commencing Term

Term 1

Total Units of Credit (UOC)

Delivery Mode

On Campus

School

Economics

Browse archives for this course

The course outline is not available for current term. To view outlines from other year and/or terms visit the archives

1. Course Details

Summary of Course

This course covers the practical use of econometric and statistical techniques applied in the business world. Building and evaluating forecasting models using time series data will be the focus of this course. Understanding these issues will allow students to formulate and use reliable forecasting models based on sound economic principles.

Teaching Times and Locations

Please note that teaching times and locations are subject to change. Students are strongly advised to refer to the Class Timetable website for the most up-to-date teaching times and locations.

View course timetable

Course Policies & Support

The Business School expects that you are familiar with the contents of this course outline and the UNSW and Business School learning expectations, rules, policies and support services as listed below:

Program Learning Outcomes
Academic Integrity and Plagiarism
Student Responsibilities and Conduct
Special Consideration
Protocol for Viewing Final Exam Scripts
Student Learning Support Services

Further information is provided in the Assessment and Policies and Support sections.

Students may not circulate or post online any course materials such as handouts, exams, syllabi or similar resources from their courses without the written permission of their instructor.

Course Aims and Relationship to Other Courses

This course is offered as part of the economics/econometrics stream in the BCom and BEc degrees. It aims to provide a foundation in business forecasting analyses based on econometric methods. Reliable long-term demand forecasts are essential input to the formulation of business plans in capital-intensive and price-regulated industries such as electricity, gas and water supply industries. This course is a prerequisite of ECON3206 Financial Econometrics.

Presumed knowledge

Pre-requisite: ECON1203 or COMM1110 or MATH1041 or MATH1231 or MATH1241 or MATH1251. It is highly recommended that students who complete COMM1110 also complete COMM1190 before enrolling in this course.

Student Learning Outcomes

The Course Learning Outcomes (CLOs) are what you should be able to demonstrate by the end of this course, if you participate fully in learning activities and successfully complete the assessment items.

CLOs also contribute to your achievement of the Program Learning Outcomes (PLOs), which are developed across the duration of a program. PLOs are, in turn, directly linked to UNSW graduate capabilities. More information on Coursework PLOs is available under Policies and Support. For PG Research PLOs, including MPDBS, please refer to the UNSW HDR Learning Outcomes.

The following table shows how the CLOs for this course relate to the overall PLOs and indicates where each CLO and PLO is assessed:

Course Learning Outcomes	Program Learning Outcomes	Course Assessment Item
On successful completion of the course, you should be able to:	This course helps you to develop the following Program Learning Outcomes:	This learning outcome will be assessed in the following items:
1. Explain various notions/concepts/principles in time series analysis and forecasting.	PLO 1: Business knowledge PLO 3: Business communication	Hand-in Problem Sets Course Project Final Exam
2. Choose and use standard techniques of time series analysis to analyse real data, and build appropriate forecasting models.	PLO 1: Business knowledge PLO 2: Problem solving PLO 3: Business communication	Hand-in Problem Sets Course Project Final Exam
3. Review and interpret modelling and forecasting results critically.	PLO 2: Problem solving PLO 3: Business communication PLO 5: Responsible business practice	Hand-in Problem Sets Course Project
4. Construct written work which is logically and professionally presented.	PLO 3: Business communication	Hand-in Problem Sets Course Project Final Exam

2. Staff Contact Details

Position	Title	Name	Email	Location	Phone	Consultation Times
Lecturer-in-charge	Prof	Kevin Fox		Room 3119, Quadrangle building	(02) 9385 3320	Wednesday 11:00-12:00 and by appointment

Communications with staff

You should feel free to contact your lecturer about any academic matter. However, for efficiency, all enquiries about the subject material should be made at lectures or tutorials or during consultation time. Discussion of course subject material will not be entered into via lengthy emails.

Student Enrolment Requests

Students can vary their own enrolment (including switching lecture streams or tutorials) via myUNSW until the end of Week 1. In general, most other student enrolment requests should be directed to The Nucleus: Student Hub (formerly Student Central). These include enrolment in full courses or tutorials, course timetable clashes, waiving prerequisites for any course, transfer-of-credit (international exchange, transfer to UNSW, cross-institutional study, etc.), or any other request which requires a decision about equivalence of courses and late enrolment for any course. Where appropriate, the request will be passed to the School Office for approval before processing. Note that enrolment changes are rarely considered after Week 2 classes have taken place.

3. Learning and Teaching Activities

Use of your Webcam and Digital Devices: If you enrol in an online class, or the online stream of a hybrid class, teaching and associated activities will be conducted using Teams, Zoom, or similar a technology. Using a webcam is optional, but highly encouraged, as this will facilitate interaction with your peers and instructors. If you are worried about your personal space being observed during a class, we encourage you to blur your background or make use of a virtual background. Please contact the Lecturer-in-Charge if you have any questions or concerns.

Some courses may involve undertaking online exams for which your own computer or digital devices will be required. Monitoring of online examinations will be conducted directly by University staff and is bound by the University's privacy and security requirements. Any data collected will be handled accordance with UNSW policies and standards for data governance. For more information on how the University manages personal information please refer to the UNSW Student Privacy Statement and the UNSW Privacy Policy.

Approach to Learning and Teaching in the Course

The philosophy underpinning this course and its teaching and learning strategies is based on the Guidelines on Learning that Inform Teaching at UNSW. Specifically, the lectures, tutorials and assessment have been designed to appropriately challenge students and support the achievement of the desired learning outcomes. A climate of inquiry and dialogue is encouraged between students and teachers and among students (in and out of class). The lecturers and tutors aim to provide meaningful and timely feedback to students to improve learning outcomes.

Learning Activities and Teaching Strategies

Lectures

Pre-prepared video recordings for the lectures will be placed on the Moodle site. Students should view these videos and related materials. It is expected that it will take students at least 90 minutes to view and review these recordings. The scheduled lecture times are Mondays 11:00-12:30 and Wednesdays 15:00-16:30. The scheduled lecture time on Mondays (11:00-12:30) can be used for viewing and reviewing these recordings. There will be an in-person session with the Lecturer on Wednesdays 15:00-16:30, during which time he will go through the lecture material in more detail, provide extra examples, and answer questions. In total, it is expected that students will spend three hours per week on the lecture materials (1.5 hours viewing and reviewing the recorded videos, plus 1.5 hours online with the lecturer on Wednesdays from 15:00 to 16:30.

The purpose of lectures is to provide a logical structure for the topics that make up the course; to emphasise the important principles/concepts/methods of each topic; and to provide relevant examples to which the principles/concepts/methods are applied.

Tutorials

There are one and a half hour tutorials each week, starting from Week 2. These are either in-person (on campus) or online, depending on the stream in which you are enrolled. Exercises will be assigned for each tutorial. Students should attempt these before attending tutorials. Along with the many examples provided in the lectures, they are the best guide to the types of questions that will be used in assessment tasks. Model answers to tutorial questions will be posted each week, after all the tutorials have been completed, providing you with feedback on how the questions should have been answered.

The tutorials are an integral part of the subject. Tutorial presentations, discussions, and solutions to problems are designed to help students deepen their understanding and practice learnt material. The tutorials will also help you learn and use the statistical package R that is used in the course.

In summary, there will be 4.5 hours of structured activities for this course each week:

1. Viewing and reviewing lecture recordings: 1.5 hours

2. Attending an online lecture with the lecturer: 1.5 hours (Wednesdays 15:00-14:30)

3. Tutorials: 1.5 hours

Statistics Computer Package R is the computer package used in the course. The lectures, tutorials and online materials will show you how to download and use R. Some of you may have already had some or extensive experience with R. If not, you will learn its use through this course.

Out-of-Class Study

While students may have preferred individual learning strategies, it is important to note that most learning will be achieved outside of class time. Lectures can only provide a structure to assist your study, and tutorial time is limited.

An “ideal” weekly strategy (on which the provision of the course materials is based) might include:

View the relevant pre-prepared video recordings and read the relevant chapter(s) of the text and lecture slides before attending the in-person lecture.
Attend the in-person lecture. Here the context of the topic in the course and the important elements of the topic are explained in more detail.
Attempt tutorial tasks and questions before attending the tutorial class. This helps you identify issues that can be discussed and resolved in the tutorial class.

4. Assessment

Formal Requirements

In order to pass this course, you must:

achieve a composite mark of at least 50 out of 100;
meet any additional requirements described in the Assessment Summary section.

You are expected to attempt all assessment requirements in the course.

Assessment Structure

Assessment Task	Weighting	Length	Due Date
Two problem sets to hand in. They count for 10% each.	20%	–	First: Due by 4pm Friday of Week 3 Second: Due by 4pm Friday of Week 5.
Course Project	25%	No longer than 20 pages including bibliography and any appendices. A separate title page is not required. At least 11 point font should be used, with adequate margins for comments. Any extra pages will not be marked.	Due by 4pm Friday of Week 9.
Final Exam	55%	approx. 2 hours	University Exam Period
Total	100%	–	–

Assessment Summary

Problem Sets (20%)

Two problem sets will count for 10% each towards the final mark. You may consult with classmates, but your write-up must be your own. Submission will be through the course Moodle site. Both your write-up and the code used must be submitted. More details, including the format and marking criteria, will be posted on the Moodle site.

Course Project (25%)

The Course Project will be a forecasting exercise with real data, to be completed individually. You may consult with classmates, but your write-up must be your own. Submission will be through the course Moodle site. Both your write-up and the code used must be submitted.

The report should be no longer than 20 pages including bibliography and any appendices. Do not include a separate title page. At least 11 point font should be used, with adequate margins for comments. Any extra pages will not be marked. More details, including the format and marking criteria, will be posted on the Moodle site.

Final Exam (55%)

The final exam will cover the entire course. All material covered in the course is examinable. It will be a take-home exam. Questions will include exercises in forecasting using actual data. It should take approx. 2 hours for a well-prepared student to complete the final exam.

Assignment Submission Procedure

Answers to assessment tasks must be submitted via links on the course Moodle site.

Assessment Feedback

Feedback on student performance from formative and summative assessment tasks will be provided to students in a timely manner. Assessment tasks completed within the teaching period of a course, other than a final assessment, will be assessed and students provided with feedback, with or without a provisional result, within 10 working days of submission, under normal circumstances. Feedback on continuous assessment tasks (e.g. laboratory and studio-based, workplace-based, weekly quizzes) will be provided prior to the midpoint of the course.

Special Consideration

You can apply for special consideration when illness or other circumstances beyond your control interfere with your performance in a specific assessment task or tasks, including online exams. Students studying remotely who have exams scheduled between 10pm and 7am local time, are also able to apply for special consideration to sit a supplementary exam at a time outside of these hours.

Special consideration is primarily intended to provide you with an extra opportunity to demonstrate the level of performance of which you are capable. To apply, and for further information, see Special Consideration on the UNSW Current Students page.

Special consideration applications will be assessed centrally by the Case Review Team, who will update the online application with the outcome and add any relevant comments. The change to the status of the application immediately sends an email to the student and to the assessor with the outcome of the application.

Please note the following:

Applications can only be made through Online Services in myUNSW. Applications will not be accepted by teaching staff. The lecturer-in-charge/course coordinator will be automatically notified when your application is processed.
Applying for special consideration does not automatically mean that you will be granted a supplementary exam or other concession.
If you experience illness or misadventure in the lead up to an exam or assessment, you must submit an application for special consideration, either prior to the examination taking place, or prior to the assessment submission deadline, except where illness or misadventure prevent you from doing so.
If your circumstances stop you from applying before your exam or assessment due date, you must apply within 3 working days of the assessment or the period covered by your supporting documentation.
Under the UNSW Fit To Sit/Submit rule, if you sit the exam/submit an assignment, you are declaring yourself well enough to do so and are cannot subsequently apply for special consideration.
If you become unwell on the day of – or during – an exam, you must stop working on your exam, advise your course coordinator or tutor and provide a medical certificate dated within 24 hours of the exam, with your special consideration application. For online exams, you must contact your course coordinator or tutor immediately via email, Moodle or chat and advise them you are unwell and submit screenshots of your conversation along with your medical certificate and application.
Special consideration requests do not allow the awarding of additional marks to students.

Further information on Business School policy and procedure can be found under “Special Consideration” on the Policies and Support page.

Late Submission Penalties

For assessments other than examinations, late submission will incur a penalty of 5% per day or part thereof (including weekends) from the due date and time. An assessment will not be accepted after 5 days (120 hours) of the original deadline unless special consideration has been approved. An assignment is considered late if the requested format, such as hard copy or electronic copy, has not been submitted on time or where the ‘wrong’ assignment has been submitted.

For assessments which account for 10% or less of the overall course grade, and where answers are immediately discussed or debriefed, the LIC may stipulate a different penalty. Details of such late penalties will be available on the course Moodle page.

Protocol for Viewing Final Exam Scripts

UNSW students have the right to view their final exam scripts, subject to a small number of very specific exemptions. The UNSW Business School has set a protocol under which students may view their final exam script. Individual schools within the Faculty may also set up a local process for viewing final exam scripts, so it is important that you check with your School. Further school-specific information may be included below.

Quality Assurance

The Business School is actively monitoring student learning and quality of the student experience in all its programs. A random selection of completed assessment tasks may be used for quality assurance, such as to determine the extent to which program learning goals are being achieved. The information is required for accreditation purposes, and aggregated findings will be used to inform changes aimed at improving the quality of Business School programs. All material used for such processes will be treated as confidential.

5. Course Resources

The website for this course is on Moodle.

TEXTBOOK
Rob J Hyndman and George Athanasopoulos (2021), Forecasting: Principles and Practice, 3rd edition, OTexts: Melbourne, Australia. The book can be viewed online for free at https://otexts.com/fpp3/

You can also purchase the book in soft and hard copy.

You may also find useful the slides based on the book at https://robjhyndman.com/teaching/

Pre-prepared lecture videos, lecture notes, slides and related resources will be available on the Moodle site.

Some other useful books that might be of reference:
Diebold, F.X. (2007), Elements of Forecasting, 4th Edition, Thomson South-Western (downloadable from the course website)

Gujarati, D.N. and Porter, D.C., Basic Econometrics, 5th Edition, McGraw Hill (downloadable).

Ord, J. K., Fildes, R., & Kourentzes, N. (2017). Principles of business forecasting (2nd ed.). Wessex Press Publishing Co. (available on Amazon)

Armstrong, J. S. (Ed.). (2001). Principles of forecasting: A handbook for researchers and practitioners. Kluwer Academic Publishers. (available on Amazon)

Newbold, P. and T. Bos (1994), Introductory Business and Economic Forecasting, 2nd Edition, International Thomson Publishing

Brockwell, P.J. and R.A. Davis (1996), Introduction to Time Series and Forecasting, Springer-Verlag
Wilson, J.H. and B. Keating (2007), Business Forecasting, 5th Edition, McGraw-Hill/Irwin

SOFTWARE
The software for the course is R and most of the exercises that you do will be in R. The assigned book uses R. R is a modern statistical language that has extensive capabilities and is free. This means that as part of the course you will master a modern computer package for data analytics that is increasingly used in business. Skills in using this software are increasingly valued.

6. Course Evaluation & Development

Feedback is regularly sought from students and continual improvements are made based on this feedback. At the end of this course, you will be asked to complete the myExperience survey, which provides a key source of student evaluative feedback. Your input into this quality enhancement process is extremely valuable in assisting us to meet the needs of our students and provide an effective and enriching learning experience. The results of all surveys are carefully considered and do lead to action towards enhancing educational quality.

The School of Economics strives to be responsive to student feedback. If you would like more information on how the design of this course and changes made to it over time have taken students’ needs and preferences into account, please contact the Director of Education at the School of Economics.

Students' course evaluations are very important for the further development of this course. Feedback provided by previous students has led to significant improvements in assessment items, review questions, exercises, and clarity of illustration.

Previous students told us that the best things about the course were:

- Very good structure and teaching style

- Practical structure of assessments

- Learning R in a practical way

- The course structure and the lecture videos were just the right length

- The lecture videos were well structured and well explained

- Due to the quality of this course delivered online, learning was fun, stimulating, and encouraging.

- The combination of succinct pre–recorded videos and a more discussion based live lecture enabled better understand of the topics and skills learnt each week.

Previous students told us that the following could be improved:

- More feedback on assessments

- More mathematical and theoretical components to help students understand how some models actually work

- More focus on interpreting results in relation to what is being learnt.

We have responded to this feedback by

- Designing assessments and marking to ensure more feedback is provided more promptly.

- Adding theoretical and mathematical components to the content.

- Designing the in-person lectures to place more focus on interpretation of results.

Consent for De-Identified Data to be Used for Secondary Research into Improving Student Experience

To enhance your student experience, researchers at UNSW conduct academic research that involves the use of de-identified student data, such as assessment outcomes, course grades, course engagement and participation, etc. Students of this course are being invited to provide their consent for their de-identified data to be shared with UNSW researchers for research purposes after the course is completed.

Providing consent for your de-identified data to be used in academic research is voluntary and not doing so will not have an impact on your course grades.

Researchers who want to access your de-identified data for future research projects will need to submit individual UNSW Ethics Applications for approval before they can access your data.

A full description of the research activities aims, risks associated with these activities and how your privacy and confidentiality will be protected at all times can be found here.

If you consent to have your de-identified data used for academic research into improving student experience, you do not need to do anything. Your consent will be implied, and your data may be used for research in a format that will not individually identify you after the course is completed.

If you do not consent for this to happen, please email the opt-out form to seer@unsw.edu.au to opt-out from having your de-identified data used in this manner. If you complete the opt-out form, the information about you that was collected during this course will not be used in academic research.

7. Course Schedule

Note: for more information on the UNSW academic calendar and key dates including study period, exam, supplementary exam and result release, please visit: https://student.unsw.edu.au/new-calendar-dates

Week	Activity	Topic	Assessment/Other
Week 1: 13 February	Lecture 1 and 2	Introduction to Forecasting Time Series Graphics	Hyndman and Athanasopoulos (2021), chapters 1 and 2
Week 2: 20 February	Lecture 1 and 2	Continuation of Time series graphics Time series decomposition	Hyndman and Athanasopoulos (2021), chapters 2 and 3
Week 2: 20 February	Tutorial	Introduction to R Exercises in R	Hyndman and Athanasopoulos (2021), Appendix: Using R
Week 3: 27 February	Lecture 1 and 2	Features of time series Some tools for forecasting	Hyndman and Athanasopoulos (2021), chapter 4 and 5 Problem Set 1 due at 4pm on Friday of this week.
Week 3: 27 February	Tutorial	More R practice Exercises time series graphics Exercises in time series decomposition	Problem solving and class participation
Week 4: 6 March	Lecture 1 and 2	Judgemental forecasts Exponential Smoothing	Hyndman and Athanasopoulos (2021), chapters 6 and 8
Week 4: 6 March	Tutorial	Look at features of time series and tools for forecasting in R Discuss previous exercises given out Review the first Problem Set	Problem solving and class participation
Week 5: 13 March	Lecture 1 and 2	ARIMA Models	Hyndman and Athanasopoulos (2021), Chapter 9 Problem Set 2 due at 4pm on Friday of this week.
Week 5: 13 March	Tutorial	Exercises in exponential smoothing in R Discuss previous exercises given out	Problem solving and class participation
Week 6: 20 March	Lecture 1 and 2	NO LECTURES	–
Week 6: 20 March	Tutorial	NO TUTORIALS	–
Week 7: 27 March	Lecture 1 and 2	Continuation of ARIMA Models	Hyndman and Athanasopoulos (2021), Chapter 9
Week 7: 27 March	Tutorial	ARIMA exercises Discuss previous exercises given out Review the second Problem Set	Problem solving and class participation
Week 8: 3 April	Lecture 1 and 2	Time Series Regression Models	Hyndman and Athanasopoulos (2021), Chapter 7
Week 8: 3 April	Tutorial	ARIMA R commands and related commands Go over some exercises on ARIMA	Problem solving and class participation
Week 9: 10 April	Lecture 1 and 2	Dynamic Regression Models	Hyndman and Athanasopoulos (2021), Chapter 10 Project submission due by 4pm on Friday of this week.
Week 9: 10 April	Tutorial	Work with time series regression models in R Discuss previous exercises given out	Problem solving and class participation
Week 10: 18 April	No lectures	NO LECTURES	–
Week 10: 18 April	Tutorial	Work with dynamic regression models in R Wrap-up and preparation for Final Exam	–

8. Policies and Support

Information about UNSW Business School program learning outcomes, academic integrity, student responsibilities and student support services. For information regarding special consideration, supplementary exams and viewing final exam scripts, please go to the key policies and support page.

Program Learning Outcomes

The Business School places knowledge and capabilities at the core of its curriculum via seven Program Learning Outcomes (PLOs). These PLOs are systematically embedded and developed across the duration of all coursework programs in the Business School.

PLOs embody the knowledge, skills and capabilities that are taught, practised and assessed within each Business School program. They articulate what you should know and be able to do upon successful completion of your degree.

Upon graduation, you should have a high level of specialised business knowledge and capacity for responsible business thinking, underpinned by ethical professional practice. You should be able to harness, manage and communicate business information effectively and work collaboratively with others. You should be an experienced problem-solver and critical thinker, with a global perspective, cultural competence and the potential for innovative leadership.

All UNSW programs and courses are designed to assess the attainment of program and/or course level learning outcomes, as required by the UNSW Assessment Design Procedure. It is important that you become familiar with the Business School PLOs, as they constitute the framework which informs and shapes the components and assessments of the courses within your program of study.

PLO 1: Business knowledge

Students will make informed and effective selection and application of knowledge in a discipline or profession, in the contexts of local and global business.

PLO 2: Problem solving

Students will define and address business problems, and propose effective evidence-based solutions, through the application of rigorous analysis and critical thinking.

PLO 3: Business communication

Students will harness, manage and communicate business information effectively using multiple forms of communication across different channels.

PLO 4: Teamwork

Students will interact and collaborate effectively with others to achieve a common business purpose or fulfil a common business project, and reflect critically on the process and the outcomes.

PLO 5: Responsible business practice

Students will develop and be committed to responsible business thinking and approaches, which are underpinned by ethical professional practice and sustainability considerations.

PLO 6: Global and cultural competence

Students will be aware of business systems in the wider world and actively committed to recognise and respect the cultural norms, beliefs and values of others, and will apply this knowledge to interact, communicate and work effectively in diverse environments.

PLO 7: Leadership development

Students will develop the capacity to take initiative, encourage forward thinking and bring about innovation, while effectively influencing others to achieve desired results.

These PLOs relate to undergraduate and postgraduate coursework programs. For PG Research PLOs, including Master of Pre-Doctoral Business Studies, please refer to the UNSW HDR Learning Outcomes

Business School course outlines provide detailed information for students on how the course learning outcomes, learning activities, and assessment/s contribute to the development of Program Learning Outcomes.

UNSW Graduate Capabilities

The Business School PLOs also incorporate UNSW graduate capabilities, a set of generic abilities and skills that all students are expected to achieve by graduation. These capabilities articulate the University’s institutional values, as well as future employer expectations.

UNSW Graduate Capabilities	Business School PLOs
Scholars capable of independent and collaborative enquiry, rigorous in their analysis, critique and reflection, and able to innovate by applying their knowledge and skills to the solution of novel as well as routine problems.	PLO 1: Business knowledge PLO 2: Problem solving PLO 3: Business communication PLO 4: Teamwork PLO 7: Leadership development
Entrepreneurial leaders capable of initiating and embracing innovation and change, as well as engaging and enabling others to contribute to change	PLO 1: Business knowledge PLO 2: Problem solving PLO 3: Business communication PLO 4: Teamwork PLO 6: Global and cultural competence PLO 7: Leadership development
Professionals capable of ethical, self-directed practice and independent lifelong learning	PLO 1: Business knowledge PLO 2: Problem solving PLO 3: Business communication PLO 5: Responsible business practice
Global citizens who are culturally adept and capable of respecting diversity and acting in a socially just and responsible way.	PLO 1: Business knowledge PLO 2: Problem solving PLO 3: Business communication PLO 4: Teamwork PLO 5: Responsible business practice PLO 6: Global and cultural competence

While our programs are designed to provide coverage of all PLOs and graduate capabilities, they also provide you with a great deal of choice and flexibility. The Business School strongly advises you to choose a range of courses that assist your development against the seven PLOs and four graduate capabilities, and to keep a record of your achievements as part of your portfolio. You can use a portfolio as evidence in employment applications as well as a reference for work or further study. For support with selecting your courses contact the UNSW Business School Student Services team.

Academic Integrity and Plagiarism

Academic Integrity is honest and responsible scholarship. This form of ethical scholarship is highly valued at UNSW. Terms like Academic Integrity, misconduct, referencing, conventions, plagiarism, academic practices, citations and evidence based learning are all considered basic concepts that successful university students understand. Learning how to communicate original ideas, refer sources, work independently, and report results accurately and honestly are skills that you will be able to carry beyond your studies.

The definition of academic misconduct is broad. It covers practices such as cheating, copying and using another person’s work without appropriate acknowledgement. Incidents of academic misconduct may have serious consequences for students.

Plagiarism

UNSW regards plagiarism as a form of academic misconduct. UNSW has very strict rules regarding plagiarism. Plagiarism at UNSW is using the words or ideas of others and passing them off as your own. All Schools in the Business School have a Student Ethics Officer who will investigate incidents of plagiarism and may result in a student’s name being placed on the Plagiarism and Student Misconduct Registers.

Below are examples of plagiarism including self-plagiarism:

Copying: Using the same or very similar words to the original text or idea without acknowledging the source or using quotation marks. This includes copying materials, ideas or concepts from a book, article, report or other written document, presentation, composition, artwork, design, drawing, circuitry, computer program or software, website, internet, other electronic resource, or another person's assignment, without appropriate acknowledgement of authorship.

Inappropriate Paraphrasing: Changing a few words and phrases while mostly retaining the original structure and/or progression of ideas of the original, and information without acknowledgement. This also applies in presentations where someone paraphrases another’s ideas or words without credit and to piecing together quotes and paraphrases into a new whole, without appropriate referencing.

Collusion: Presenting work as independent work when it has been produced in whole or part in collusion with other people. Collusion includes:

Students providing their work to another student before the due date, or for the purpose of them plagiarising at any time
Paying another person to perform an academic task and passing it off as your own
Stealing or acquiring another person’s academic work and copying it
Offering to complete another person’s work or seeking payment for completing academic work

Collusion should not be confused with academic collaboration (i.e., shared contribution towards a group task).

Inappropriate Citation: Citing sources which have not been read, without acknowledging the 'secondary' source from which knowledge of them has been obtained.

Self-Plagiarism: ‘Self-plagiarism’ occurs where an author republishes their own previously written work and presents it as new findings without referencing the earlier work, either in its entirety or partially. Self-plagiarism is also referred to as 'recycling', 'duplication', or 'multiple submissions of research findings' without disclosure. In the student context, self-plagiarism includes re-using parts of, or all of, a body of work that has already been submitted for assessment without proper citation.

To see if you understand plagiarism, do this short quiz: https://student.unsw.edu.au/plagiarism-quiz

Cheating

The University also regards cheating as a form of academic misconduct. Cheating is knowingly submitting the work of others as their own and includes contract cheating (work produced by an external agent or third party that is submitted under the pretences of being a student’s original piece of work). Cheating is not acceptable at UNSW.

If you need to revise or clarify any terms associated with academic integrity you should explore the 'Working with Academic Integrity' self-paced lessons available at: https://student.unsw.edu.au/aim.

For UNSW policies, penalties, and information to help you avoid plagiarism see: https://student.unsw.edu.au/plagiarism as well as the guidelines in the online ELISE tutorials for all new UNSW students: http://subjectguides.library.unsw.edu.au/elise. For information on student conduct see: https://student.unsw.edu.au/conduct.

For information on how to acknowledge your sources and reference correctly, see: https://student.unsw.edu.au/referencing. If you are unsure what referencing style to use in this course, you should ask the lecturer in charge.

Student Responsibilities and Conduct

Students are expected to be familiar with and adhere to university policies in relation to class attendance and general conduct and behaviour, including maintaining a safe, respectful environment; and to understand their obligations in relation to workload, assessment and keeping informed.

Information and policies on these topics can be found on the 'Managing your Program' website.

Workload

It is expected that you will spend at least ten to twelve hours per week studying for a course except for Summer Term courses which have a minimum weekly workload of twenty to twenty four hours. This time should be made up of reading, research, working on exercises and problems, online activities and attending classes. In periods where you need to complete assignments or prepare for examinations, the workload may be greater. Over-commitment has been a cause of failure for many students. You should take the required workload into account when planning how to balance study with employment and other activities.

We strongly encourage you to connect with your Moodle course websites in the first week of semester. Local and international research indicates that students who engage early and often with their course website are more likely to pass their course.

View more information on expected workload

Attendance and Engagement

Your regular attendance and active engagement in all scheduled classes and online learning activities is expected in this course. Failure to attend / engage in assessment tasks that are integrated into learning activities (e.g. class discussion, presentations) will be reflected in the marks for these assessable activities. The Business School may refuse final assessment to those students who attend less than 80% of scheduled classes where attendance and participation is required as part of the learning process (e.g. tutorials, flipped classroom sessions, seminars, labs, etc.). If you are not able to regularly attend classes, you should consult the relevant Course Authority.

View more information on attendance

General Conduct and Behaviour

You are expected to conduct yourself with consideration and respect for the needs of your fellow students and teaching staff. Conduct which unduly disrupts or interferes with a class, such as ringing or talking on mobile phones, is not acceptable and students may be asked to leave the class.

View more information on student conduct

Health and Safety

UNSW Policy requires each person to work safely and responsibly, in order to avoid personal injury and to protect the safety of others.

View more information on Health and Safety

Keeping Informed

You should take note of all announcements made in lectures, tutorials or on the course web site. From time to time, the University will send important announcements to your university e-mail address without providing you with a paper copy. You will be deemed to have received this information. It is also your responsibility to keep the University informed of all changes to your contact details.

Student Support and Resources

The University and the Business School provide a wide range of support services and resources for students, including:

Business School Learning Support Tools
Business School provides support a wide range of free resources and services to help students in-class and out-of-class, as well as online. These include:

Academic Communication Essentials – A range of academic communication workshops, modules and resources to assist you in developing your academic communication skills.
Learning consultations – Meet learning consultants who have expertise in business studies, literacy, numeracy and statistics, writing, referencing, and researching at university level.
PASS classes – Study sessions facilitated by students who have previously and successfully completed the course.
Educational Resource Access Scheme – To support the inclusion and success of students from equity groups enrolled at UNSW Sydney in first year undergraduate Business programs.

The Nucleus - Business School Student Services team
The Nucleus Student Services team provides advice and direction on all aspects of enrolment and graduation. Level 2, Main Library, Kensington 02 8936 7005 / https://nucleus.unsw.edu.au/en/contact-us

Business School Equity, Diversity and Inclusion
The Business School Equity, Diversity and Inclusion Committee strives to ensure that every student is empowered to have equal access to education. The Business School provides a vibrant, safe, and equitable environment for education, research, and engagement that embraces diversity and treats all people with dignity and respect. BUSEDI@unsw.edu.au

UNSW Academic Skills
Resources and support – including workshops, individual consultations and a range of online resources – to help you develop and refine your academic skills. See their website for details.
academicskills@unsw.edu.au

Student Support Advisors
Student Support Advisors work with all students to promote the development of skills needed to succeed at university, whilst also providing personal support throughout the process.
John Goodsell Building, Ground Floor.
advisors@unsw.edu.au
02 9385 4734

International Student Support
The International Student Experience Unit (ISEU) is the first point of contact for international students. ISEU staff are always here to help with personalised advice and information about all aspects of university life and life in Australia.
Advisors can support you with your student visa, health and wellbeing, making friends, accommodation and academic performance.
International.student@unsw.edu.au
02 9385 4734

Equitable Learning Services
Equitable Learning Services (formerly Disability Support Services) is a free and confidential service that provides practical support to ensure that your health condition doesn't adversely affect your studies. Register with the service to receive educational adjustments.
Ground Floor, John Goodsell Building.
els@unsw.edu.au
02 9385 4734

UNSW Counselling and Psychological Services
Provides support and services if you need help with your personal life, getting your academic life back on track or just want to know how to stay safe, including free, confidential counselling.
Level 2, East Wing, Quadrangle Building.
counselling@unsw.edu.au
02 9385 5418

Library services and facilities for students
The UNSW Library offers a range of collections, services and facilities both on-campus and online.
Main Library, F21.
02 9065 9444

Moodle eLearning Support
Moodle is the University’s learning management system. You should ensure that you log into Moodle regularly.
externalteltsupport@unsw.edu.au
02 9385 3331

UNSW IT
UNSW IT provides support and services for students such as password access, email services, wireless services and technical support.
UNSW Library Annexe (Ground floor).
02 9385 1333

Support for Studying Online

The Business School and UNSW provide a wide range of tools, support and advice to help students achieve their online learning goals.

The UNSW Guide to Online Study page provides guidance for students on how to make the most of online study.

We recognise that completing quizzes and exams online can be challenging for a number of reasons, including the possibility of technical glitches or lack of reliable internet. We recommend you review the Online Exam Preparation Checklist of things to prepare when sitting an online exam.

Save as PDF

Select the sections you wish to include in the Course Outline PDF.

Save as PDF

Previous Next

Browse archives for this course

Accreditation

ECON2209 Business Forecasting - 2023

Browse archives for this course

1. Course Details

Summary of Course

Teaching Times and Locations

Course Policies & Support

Course Aims and Relationship to Other Courses

Presumed knowledge

Student Learning Outcomes

2. Staff Contact Details

Communications with staff

Student Enrolment Requests

3. Learning and Teaching Activities

Approach to Learning and Teaching in the Course

Learning Activities and Teaching Strategies

Lectures

Tutorials

Out-of-Class Study

4. Assessment

Formal Requirements

Assessment Structure

Assessment Summary

Problem Sets (20%)

Course Project (25%)

Final Exam (55%)

Assignment Submission Procedure

Assessment Feedback

Special Consideration

Protocol for Viewing Final Exam Scripts

Quality Assurance

5. Course Resources

6. Course Evaluation & Development

Consent for De-Identified Data to be Used for Secondary Research into Improving Student Experience

7. Course Schedule

8. Policies and Support

UNSW Graduate Capabilities

Plagiarism

Cheating

Workload

Attendance and Engagement

General Conduct and Behaviour

Health and Safety

Keeping Informed

Save as PDF

Browse archives for this course