1. Handbook
  2. Subjects
  3. Quantitative Methods 2
  4. Print

Quantitative Methods 2 (ECON20003)

Undergraduate level 2Points: 12.5On Campus (Parkville)

You’re viewing the 2023 Handbook:
Or view archived Handbooks
Undergraduate programs will be delivered on campus. Graduate programs will mainly be delivered on campus, with dual-delivery and online options available to a select number of subjects within some programs.
To learn more, visit 2023 Course and subject delivery.

Overview

Availability
Summer Term
Semester 1
Semester 2
FeesLook 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

 On completion of the subject, students should be able to:

  • 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

  • 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.

  • Moderate level of development: oral communication; written communication; problem solving; critical thinking; receptiveness to alternative ideas.

  • Some level of development: team work; accessing data and other information from a range of sources.

Last updated: 7 September 2023

Eligibility and requirements

Prerequisites

One of

Code Name Teaching period Credit Points
ECON10005 Quantitative Methods 1
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
MAST10010 Data Analysis 1
Semester 2 (On Campus - Parkville)
 12.5
MAST10011 Experimental Design and Data Analysis
Semester 1 (On Campus - Parkville)
 12.5
MAST20004 Probability
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
 12.5
MAST20006 Probability for Statistics
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: 7 September 2023

Assessment

DescriptionTimingPercentage

Assignment (involving quantitative data analysis and review, including graphs, charts and equations)

  • 10 pages
Week 55%

Assignment (involving quantitative data analysis and review, including graphs, charts and equations)

  • 10 pages
Week 95%

Assignment (involving quantitative data analysis and review, including graphs, charts and equations)

  • 10 pages
Week 125%

Mid-semester test (online, covering material prior to week 6)

  • 30 minutes
Week 65%

Tutorial participation (including completion of weekly tutorial exercises involving quantitative data analysis and review)

Throughout the teaching period10%

End-of-semester examination

  • 2 hours
Hurdle requirement: To pass this subject students must pass the end of semester examination.		During the examination period70%

Last updated: 7 September 2023

Dates & times

  • Summer Term
    Principal coordinatorDavid Moreton
    Mode of deliveryOn Campus (Parkville)
    Contact hoursTwo 2-hour lectures and two 1-hour tutorials per week for six weeks
    Total time commitment170 hours
    Teaching period 3 January 2023 to 17 February 2023
    Last self-enrol date12 January 2023
    Census date20 January 2023
    Last date to withdraw without fail 3 February 2023
    Assessment period ends25 February 2023

    Summer Term contact information

    David Moreton: dmoreton@unimelb.edu.au

  • Semester 1
    Principal coordinatorMehmet Ozmen
    Mode of deliveryOn Campus (Parkville)
    Contact hoursTwo 1-hour lectures, one 1-hour tutorial and one 1-hour workshop
    Total time commitment170 hours
    Teaching period27 February 2023 to 28 May 2023
    Last self-enrol date10 March 2023
    Census date31 March 2023
    Last date to withdraw without fail 5 May 2023
    Assessment period ends23 June 2023

    Semester 1 contact information

    Mehmet Ozmen: mehmet.ozmen@unimelb.edu.au

  • Semester 2
    Principal coordinatorMehmet Ozmen
    Mode of deliveryOn Campus (Parkville)
    Contact hoursTwo 1-hour lectures, one 1-hour tutorial and one 1-hour workshop
    Total time commitment170 hours
    Teaching period24 July 2023 to 22 October 2023
    Last self-enrol date 4 August 2023
    Census date31 August 2023
    Last date to withdraw without fail22 September 2023
    Assessment period ends17 November 2023

    Semester 2 contact information

    Mehmet Ozmen: mehmet.ozmen@unimelb.edu.au

Time commitment details

170 Hours

What do these dates mean

Visit this webpage to find out about these key dates, including how they impact on:

  • Your tuition fees, academic transcript and statements.
  • And for Commonwealth Supported students, your:
    - Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
    - Completion rate. Students who started their course from 2022 and are in a CSP or receiving a HELP Loan (eg FEE-HELP) must meet the completion rate to continue to receive Commonwealth Support for that course.

Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement, and as a fail toward the completion rate, unless there are approved ‘special circumstances’.

Last updated: 7 September 2023

Further information

Last updated: 7 September 2023