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Quantitative Methods 1 (ECON10005)
Undergraduate level 1Points: 12.5On Campus (Parkville)
About this subject
Contact information
Summer Term
Chin Yong Quek: cy.quek@unimelb.edu.au
Semester 1
Tomasz Wozniak: tomasz.wozniak@unimelb.edu.au
Wasana Karunarathne: lakminik@unimelb.edu.au
Semester 2
Jenny Williams: jenny.williams@unimelb.edu.au
Heidi Quah: heidi.quah@unimelb.edu.au
Overview
| Availability | Summer Term - On Campus Semester 1 - On Campus Semester 2 - On Campus |
|---|---|
| Fees | Look up fees |
This subject develops skills in descriptive and inferential statistical analysis that underpin data-informed decision-making in the various specializations within the faculty. It provides a foundation for all second-year quantitative subjects in the commerce degree. The topics covered include describing data visually and numerically; probability and probability distributions for discrete and continuous random variables; sampling distributions and estimation; hypothesis testing for one and two samples, and simple regression. Practical examples are drawn from economics, management, marketing, accounting, and finance. Students will gain experience in the use of Excel to visualise and communicate key features of data, and in the use of data to inform decisions made in business and economics.
Intended learning outcomes
On completion of this subject, students should be able to:
- Graph economic data using methods that facilitate analysis.
- Explain concepts relevant for summarising and interpreting data.
- Explain how the concepts of random variables and probability distributions are useful for drawing inferences.
- Explain the concepts of population, samples and sampling distributions.
- Estimate unknown population quantities and test hypotheses about them.
- Conduct simple regression analysis to model the relationship between variables and draw inferences about relationships.
- Apply common analytical techniques relevant for financial decision making.
Generic skills
On successful completion of this subject, students should be able to:
- High level of development: problem solving; 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; accessing data and other information from a range of sources.
- Moderate level of development: oral communication; written communication; critical thinking; receptiveness to alternative ideas.
- Some level of development: collaborative learning; team work.
Last updated: 11 December 2025