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Quantitative Methods 2 (ECON20003)
Undergraduate level 2Points: 12.5On Campus (Parkville)
About this subject
Contact information
Summer Term
Email: dmoreton@unimelb.edu.au
Semester 1
Email: l.konya@unimelb.edu.au
Semester 2
Email: l.konya@unimelb.edu.au
Overview
Availability | Summer Term Semester 1 Semester 2 |
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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: 3 October 2024