• Class Number 4214
  • Term Code 3250
  • Class Info
  • Unit Value 0 units
  • Mode of Delivery Online
  • COURSE CONVENER
    • Prof Robert Breunig
  • LECTURER
    • Prof Robert Breunig
  • Class Dates
  • Class Start Date 23/06/2022
  • Class End Date 22/07/2022
  • Census Date 15/07/2022
  • Last Date to Enrol 15/07/2022
SELT Survey Results

The aim of this course is to prepare students for the Econometric Techniques subject (IDEC8017) and other econometric related study or research in the IDEC Master of International and Development Economics Program. The course is designed to provide fundamental knowledge in probability theory, statistics and econometric techniques. There will also be two computer sessions on using the STATA software package. As a preparatory course, the class environment will be structured to help students become familiar with the ANU teaching environment, resources available to students, and requirements of formal coursework. In-class exercises are an important component of teaching in the course. Student participation in discussion of issues in econometrics and statistics, and study at ANU more broadly, is also highly encouraged.

Required Resources

Required Readings

Part A: Mathematics 

  • Hoy, M., Livernois, J., McKenna, C., Rees, R., & Stengos, T. (2011). Mathematics for Economics. MIT press. (Chapters 2-13)

Part B: Statistics

  • Wooldridge, J. M. (2012). Introductory Econometrics: A Modern Approach, (Boston: Cengage Learning). (Appendices B, C; Chapters 1-4).

See Wattle Page for Course

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

This course is split into two components: Part A Mathematics and Part B Statistics. 

Part A provides students with basic mathematical tools which will be intensively used in Mathermatics, Econometrics and Microeconomics. This part focuses on linear algebra, function, derivative, differential and optimization. Upon the completion of these topics, students are expected to be able to:

1.     work with simple matrix operations

2.     write a system of linear equations under matrix form and solve the system of equations

3.     estimate the impact of a change in one variable on the other variable through marginal effect and elasticity

4.     apply the Lagrangian method to solve for cost minimization, utility maximization and profitmaximization

Part B is designed to give students a knowledge of the fundamentals of Probability and Mathematical Statistics and an introduction to econometrics. The objectives for students in Part B Statistics are to:

5.     have fundamental knowledge of probability theory, statistics and mathematics required for studying econometrics

6.     construct, test, and analyse simple statistics and econometric models, using variables and relationships commonly found in studies of economic theory

7.     identify the desirable properties of estimators

8.     identify key classical assumptions in the field of econometrics

9.     understand the least squares method in measuring the relationship between one or more than one explanatory variable and a dependent variable

R training session is added to Part B in order to provide students with a useful and powerful instrument for data computation and quantitative analysis.

Class Schedule

Week/Session Summary of Activities Assessment
1 Part A - Topic 1: Linear Algebra Learning outcomes: A1: Work with simple matrix operations A2: Set up a system of linear equations in matrix form and solve the system of equations
2 Part A - Topic 2: Function and Calculus Learning outcomes: A3: Estimate the impact of a change in one variable on the other variable through marginal effect and elasticity.
3 Part A - Topic 3: Optimization Learning outcomes: A4: Apply the Lagrangian method to solve for cost minimization, utility maximization, and profit maximization
4 Part B - Topic 4: Fundamentals of probability Learning outcomes: B1: Have a fundamental knowledge of probability, statistic, and mathematics ready for studying econometrics
5 Part B - Topic 5: Fundamentals of mathematical statistics Learning outcomes: B2: Construct, test, and analyse simple statistics and econometric models, using variables and relationships commonly found in studies of economic theory. B3: Identify the desirable properties of estimators
6 Part B - Topic 6: Econometrics & R-training session Learning outcomes: B4: Identify key classical assumptions in econometric models B5: Understand the least squares method in measuring the relationship between one or more than one explanatory variable and a dependent variable B6: Use R in matrix calculation and OLS regression

Tutorial Registration

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Quiz 1 20 % 24/06/2021 24/06/2021 A1 - A3
Part A Exam 30 % 28/06/2021 28/06/2021 A1 - A4
Quiz 2 20 % 14/07/2021 14/07/2021 B1 - B3
Part B Exam 30 % 16/07/2021 16/07/2021 B1 - B5

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details

Policies

ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Value: 20 %
Due Date: 24/06/2021
Return of Assessment: 24/06/2021
Learning Outcomes: A1 - A3

Quiz 1

Learning Outcomes:

A1. Work with simple matrix operations.

A2. Write a system of linear equations under matrix form and solve the system of equations.

A3. Estimate the impact of a change in one variable on the other variable through marginal effect and elasticity.

Assessment Task 2

Value: 30 %
Due Date: 28/06/2021
Return of Assessment: 28/06/2021
Learning Outcomes: A1 - A4

Part A Exam

Learning Outcomes:

A1. Work with simple matrix operations.

A2. Write a system of linear equations under matrix form and solve the system of equations.

A3. Estimate the impact of a change in one variable on the other variable through marginal effect and elasticity.

A4. Apply the Lagrangian method to solve for cost minimization, utility maximization and profit maximization.

Assessment Task 3

Value: 20 %
Due Date: 14/07/2021
Return of Assessment: 14/07/2021
Learning Outcomes: B1 - B3

Quiz 2

Learning Outcomes:

B1. Have fundamental knowledge of probability theory, statistics and mathematics required for studying econometrics.

B2. Construct, test, and analyse simple statistics and econometric models, using variables and relationships commonly found in studies of economic theory.

B3. Identify the desirable properties of estimators.

Assessment Task 4

Value: 30 %
Due Date: 16/07/2021
Return of Assessment: 16/07/2021
Learning Outcomes: B1 - B5

Part B Exam

Learning Outcomes:

B1. Have fundamental knowledge of probability theory, statistics and mathematics required for studying econometrics.

B2. Construct, test, and analyse simple statistics and econometric models, using variables and relationships commonly found in studies of economic theory.

B3. Identify the desirable properties of estimators.

B4. Identify key classical assumptions in the field of econometrics.

B5. Understand the least squares method in measuring the relationship between one or more than one explanatory variable and a dependent variable.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.


The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.


The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.

 

The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

  • Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
  • Late submission permitted. Late submission of assessment tasks without an extension are penalised at the rate of 5% of the possible marks available per working day or part thereof. Late submission of assessment tasks is not accepted after 10 working days after the due date, or on or after the date specified in the course outline for the return of the assessment item. Late submission is not accepted for take-home examinations.

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Prof Robert Breunig
u9809765@anu.edu.au

Research Interests


Prof Robert Breunig

By Appointment
Prof Robert Breunig
02 6125 0093
Robert.Breunig@anu.edu.au

Research Interests


Prof Robert Breunig

By Appointment

Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions