Quantitative Methods 2 (ECON20003)

Undergraduate level 2Points: 12.5On Campus (Parkville)

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Overview

Availability
Semester 1
Semester 2
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This subject provides students with core statistical skills and business analytic tools to produce innovative solutions in finance, marketing, economics and related areas. Theoretical models discussed are motivated by real-life business applications and decision problems. Practical skills in applying techniques are developed using software and focuses on conducting reproducible analyses.  

Intended learning outcomes

On successful completion of this subject, students should be able to:

  • Apply key theories and concepts in business statistics to analyse relationships between business variables via a range of quantitative models and methods;
  • Critically evaluate and validate quantitative models, test their assumptions, identify their limitations and explore solutions to estimation problems;
  • Explore data and perform data analysis using contemporary computing software; and
  • Clearly articulate statistical insights to develop evidence-based solutions to business problems. Communicate these effectively, professionally and ethically to a variety of audiences.

Generic skills

On successful completion of this subject, students should have improved the following 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: 20 March 2025

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
Semester 2 (On Campus - Parkville)
 12.5
MAST10011 Experimental Design and Data Analysis No longer available
MAST20004 Probability
Semester 1 (On Campus - Parkville)
Semester 2 (On Campus - Parkville)
 12.5
MAST20006 Probability for Statistics
Semester 1 (On Campus - Parkville)
Semester 2 (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: 20 March 2025

Assessment

DescriptionTimingPercentage

Assignment 1 (groups of 3-4)

  • 1000 words (total)
Week 510%

Assignment 2 (groups of 3-4)

  • 1000 words (total)
Week 910%

Assignment 3 (groups of 3-4)

  • 1000 words (total)
Week 1210%

Mid-semester test

  • 30 minutes
Week 610%

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 period50%

Last updated: 20 March 2025

Dates & times

  • Semester 1
    Principal coordinatorMehmet Ozmen
    Mode of deliveryOn Campus (Parkville)
    Contact hoursTwo 1-hour lectures, one 1-hour tutorial and one 1-hour workshop per week
    Total time commitment170 hours
    Teaching period 3 March 2025 to 1 June 2025
    Last self-enrol date14 March 2025
    Census date31 March 2025
    Last date to withdraw without fail 9 May 2025
    Assessment period ends27 June 2025

    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 per week
    Total time commitment170 hours
    Teaching period28 July 2025 to 26 October 2025
    Last self-enrol date 8 August 2025
    Census date 1 September 2025
    Last date to withdraw without fail26 September 2025
    Assessment period ends21 November 2025

    Semester 2 contact information

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

Time commitment details

170 hours

What do these dates mean

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Last updated: 20 March 2025

Further information

Last updated: 20 March 2025