ECON1003: Semester 1, 2020

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Units ECON1003 Semester 1 2020 [Normal day]

Unit of study_

ECON1003: Quantitative Methods in Economics

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

Overview

This unit of study provides an introduction to the quantitative methods used in economics and business. Emphasis is placed on developing the skills to set up models to study real-world phenomena, using appropriate techniques to manipulate and analyse these models and their economic interpretation. In this unit particular emphasis will be placed on the intuition of the models studied, making extensive use of a range of economic examples and business applications. It is important to note that while mathematical techniques are used in this unit, this unit is not intended as a substitute for mathematics units offered by the School of Mathematics and Statistics. Students wishing to pursue further study in mathematics, such as a major in mathematics, should consult the Faculty of Science Handbook for offerings by the School of Mathematics and Statistics. Note this unit is not available to students from the Faculty of Science.

Unit details and rules

Unit code	ECON1003
Academic unit	Economics
Credit points	6
Prohibitions ?	MATH1111 or MATH1011 or MATH1001 or MATH1901 or MATH1906
Prerequisites ?	None
Corequisites ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Mert Kimya, mert.kimya@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam	Final exam (take home) Take home exam	50%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Quizzes N/A	15%	Multiple weeks	20 to 40 minutes each
Outcomes assessed:
In-semester test	Mid-semester exam (take home) Take home exam	35%	Week 07 Due date: 09 Apr 2020 at 14:00	70 minutes
Outcomes assessed:

Assessment summary

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
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
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.

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	The straight line	Lecture (2 hr)
Week 02	Non-linear functions	Lecture (2 hr)
Week 02	The straight line	Tutorial (1 hr)
Week 03	Arithmetic and geometric sequences and series	Lecture (2 hr)
Week 03	Non-linear functions	Tutorial (1 hr)
Week 04	Financial mathematics	Lecture (2 hr)
Week 04	Arithmetic and geometric sequences and series	Tutorial (1 hr)
Week 05	Differentiation with a single variable	Lecture (2 hr)
Week 05	Financial mathematics	Tutorial (1 hr)
Week 06	Optimization with a single variable	Lecture (2 hr)
Week 06	Differentiation with a single variable	Tutorial (1 hr)
Week 07	Optimization with a single variable	Tutorial (1 hr)
Week 08	Multi-variable optimization	Lecture (2 hr)
Week 08	Multi-variable optimization	Tutorial (1 hr)
Week 09	Constrained optimization and Lagrange multipliers	Lecture (2 hr)
Week 09	Constrained optimization and Lagrange multipliers	Tutorial (1 hr)
Week 10	Integration I	Lecture (2 hr)
Week 10	Integration I	Tutorial (1 hr)
Week 11	Integration II	Lecture (2 hr)
Week 11	Integration II	Tutorial (1 hr)
Week 12	Matrices, system of equations and determinants	Lecture (2 hr)
Week 12	Matrices, system of equations and determinants	Tutorial (1 hr)
Week 13	Cramer's rule, inverse matrices and system of equations	Lecture (2 hr)
Week 13	Cramer's rule, inverse matrices and system of equations	Tutorial (1 hr)

Attendance and class requirements

Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

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.

Required textbook: Bradley ,T 2013, Essential Mathematics for Economics and Business, 4th Edition, John Wiley and Sons, Chichester.

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. demonstrate quantitative skills necessary for the economic analysis and modeling
LO2. develop logical arguments for analysis of complex problems in economics and business
LO3. demonstrate an ability to problem solve.

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.

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

Disclaimer

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