- Class Number 1218
- Term Code 3020
- Class Info
- Unit Value 0 units
- Mode of Delivery In Person
- Dr Larry Weifeng Liu
- Quoc Anh Ho
- Class Dates
- Class Start Date 13/01/2020
- Class End Date 21/02/2020
- Census Date 14/02/2020
- Last Date to Enrol 14/02/2020
This course introduces fundamental mathematical techniques to be used in applied economics. It serves as a preparation for students who will continue to do Mathematical Methods in Applied Economics (IDEC8015) and Graduate Diploma Microeconomics (IDEC 8016). The course covers topics on linear algebra and calculus. It gives students a taste of applying mathematics in economic analysis. Students are encouraged to actively participate in class discussions.
Part A: Mathematics
- Hoy, M., Livernois, J., McKenna, C., Rees, R., & Stengos, T. (2011). Mathematics for Economics. MIT press. (Chapter 2, 3, 5-7, 9-13)
Part B: Statistics
- Wooldridge, J. M. (2012). Introductory Econometrics: A Modern Approach, (Boston: Cengage Learning). (Appendix A, B, C; Chapter 1-5).
Staff FeedbackStudents will be given feedback in the following forms in this course:
- Written comments
- Verbal comments
- Feedback to the whole class, to groups, to individuals, focus groups
Student FeedbackANU 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). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
|Week/Session||Summary of Activities||Assessment|
|1||Part A, Topic 1 Linear Algebra||Students are expected to be able to A1: Simple matrix operations A2: Set up a system of linear equations in matrix form and solve for the system|
|2||Part A, Topic 2 Functions and Calculus||A3: Estimate and interpret marginal effect and elasticity|
|3||Part A, Topic 3 Optimization||A4: Apply the Lagrangian method to solve for cost minimization, utility maximization, and profit maximization|
|4||Part B, Topic 1 Fundamentals of probability||B1: Have a fundamental knowledge of probability, statistic, and mathematics ready for studying econometrics|
|5||Part B, Topic 2 Fundamentals of mathematical statistics||B2: Construct, test, and analyze the statistical hypothesis B3: Identify the desirable properties of estimators|
|6||Part B, Topic 3 Introduction to Econometrics; R training session||B4: Identify key classical assumptions in econometric models B5: Understand the OLS method in measuring the relationship among variables in the economic theory B6: Use R in matrix calculation and OLS regression|
|Assessment task||Value||Due Date||Return of assessment||Learning Outcomes|
|Quiz 1||10 %||23/01/2019||30/01/2019||A1 - A3|
|Part A Exam||40 %||28/01/2019||07/02/2019||A1 - A4|
|Quiz 2||10 %||03/02/2019||07/02/2019||B1 - B2|
|Part B Exam||40 %||10/02/2019||17/02/2019||B1 - B5|
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
PoliciesANU 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 Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
Assessment RequirementsThe 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 ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.
Moderation of AssessmentMarks 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
Learning Outcomes: A1 - A3
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.
Assessment Task 2
Learning Outcomes: A1 - A4
Part A Exam
4. Work with simple matrix operations.
5. Write a system of linear equations under matrix form and solve the system of equations.
6. Estimate the impact of a change in one variable on the other variable through marginal effect and elasticity.
7. Apply the Lagrangian method to solve for cost minimization, utility maximization and profit maximization.
Assessment Task 3
Learning Outcomes: B1 - B2
1. Have fundamental knowledge of probability theory, statistics and mathematics required for studying econometrics.
2. Construct, test, and analyse simple statistics and econometric models, using variables and relationships commonly found in studies of economic theory.
3. Identify the desirable properties of estimators.
4. Identify key classical assumptions in the field of econometrics.
Assessment Task 4
Learning Outcomes: B1 - B5
Part B Exam
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.
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