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Quantitative Methods 2 (ECON20003)
Undergraduate level 2Points: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Overview
Availability | Summer Term Semester 1 Semester 2 |
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Fees | Look up fees |
This subject provides students with background mathematical and statistical skills necessary for solving a wide range of commerce problems. It draws heavily on examples from accounting, management and marketing and, to a lesser extent, economics and finance. Topics include: review of statistics; tests of the location of populations; simple and multiple regression for use with time series and cross section data, including interpretation of estimates, hypothesis testing and forecasting, an introduction to diagnostics; Logit models; an introduction to time series methods; autoregressive distributed lag models and testing for stationarity.
Intended learning outcomes
- Conduct and interpret a number of parametric and non-parametric tests of the location of quantitative populations.
- Complete simple and multiple regression analysis, appropriate tests on regression coefficients, analyse and interpret the results and explain the findings.
- Identify the circumstances under which test procedures may not be valid.
- Analyse several specific models often employed in the various fields within commerce.
- Identify the circumstances under which a model with a binary dependent variable is appropriate.
- Evaluate the results of a Logit model, test relevant hypotheses on the regression coefficients in a Logit model and explain the findings.
- Explain the difficulties that can arise when studying time series data.
- Analyse autoregressive distributed lag models and testing for stationarity.
- Employ several methods to analyse and forecast time series data.
- Use and understand various publicly available statistics, including the many data series available describing the economy and markets.
Generic skills
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High level of development: collaborative learning; statistical reasoning; application of theory to practice; interpretation and analysis; synthesis of data and other information; evaluation of data and other information; use of computer software.
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Moderate level of development: oral communication; written communication; problem solving; critical thinking; receptiveness to alternative ideas.
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Some level of development: team work; accessing data and other information from a range of sources.
Last updated: 22 March 2024
Eligibility and requirements
Prerequisites
One of the following:
Code | Name | Teaching period | Credit Points |
---|---|---|---|
MAST10010 | Data Analysis 1 | Semester 2 (On Campus - Parkville) |
12.5 |
MAST10011 | Experimental Design and Data Analysis |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
MAST20004 | Probability | Semester 1 (On Campus - Parkville) |
12.5 |
MAST20006 | Probability for Statistics | Semester 1 (On Campus - Parkville) |
12.5 |
ECON10005 | Quantitative Methods 1 |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
Corequisites
None
Non-allowed subjects
None
Recommended background knowledge
Please refer to Prerequisites and Corequisites.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 22 March 2024
Assessment
Additional details
- Three group assignments where students can choose whether they be in a group of one or two, preparing assignments that involve quantitative data analysis and review, with each assignment not exceeding 14 pages (including graphs, charts and equations), due in weeks 5, 9 and 11, (5% each, total 15%)
- A mid-semester online test on material covered prior to week 6, in week 6, (5%)
- Tutorial participation, including completion of weekly tutorial exercises involving quantitative data analysis and review, throughout semester, (10%)
- A 2-hour end-of-semester final examination covering the whole semester's work, end of semester, (70%)
- To pass this subject students must pass the end of semester examination.
Last updated: 22 March 2024
Dates & times
- Summer Term
Principal coordinator David Moreton Mode of delivery On Campus (Parkville) Contact hours Semester 1 and 2: Two 1-hour lectures and a 1-hour tutorial per week; Summer Semester: Two 2-hour lectures and two 1-hour tutorials per week for six weeks Total time commitment 170 hours Teaching period 2 January 2018 to 16 February 2018 Last self-enrol date 11 January 2018 Census date 12 January 2018 Last date to withdraw without fail 9 February 2018 Assessment period ends 24 February 2018 - Semester 1
Principal coordinator Bill Griffiths Mode of delivery On Campus (Parkville) Contact hours Semester 1 and 2: Two 1-hour lectures and a 1-hour tutorial per week; Summer Semester: Two 2-hour lectures and two 1-hour tutorials per week for six weeks Total time commitment 170 hours Teaching period 26 February 2018 to 27 May 2018 Last self-enrol date 9 March 2018 Census date 31 March 2018 Last date to withdraw without fail 4 May 2018 Assessment period ends 22 June 2018 - Semester 2
Mode of delivery On Campus (Parkville) Contact hours Semester 1 and 2: Two 1-hour lectures and a 1-hour tutorial per week; Summer Semester: Two 2-hour lectures and two 1-hour tutorials per week for six weeks Total time commitment 170 hours Teaching period 23 July 2018 to 21 October 2018 Last self-enrol date 3 August 2018 Census date 31 August 2018 Last date to withdraw without fail 21 September 2018 Assessment period ends 16 November 2018
Time commitment details
170 Hours
Last updated: 22 March 2024
Further information
- Texts
Prescribed texts
You will be advised of prescribed texts by your lecturer.
- Related Handbook entries
This subject contributes to the following:
Type Name Major Economics Breadth Track Economics and Finance Breadth Track Quantitative Methods in Economics - Breadth options
This subject is available as breadth in the following courses:
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Last updated: 22 March 2024