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Property Data and Tools (ABPL90398)

Graduate courseworkPoints: 12.5On Campus (Parkville)

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Overview

Year of offer2017
Subject levelGraduate coursework
Subject codeABPL90398
Campus
Parkville
Availability
Semester 2
FeesSubject EFTSL, Level, Discipline & Census Date

Property Data and Tools is focused on teaching students about changes in the urban built environment and property markets through a hands-on analysis approach.

The main aims of this subject include:

  1. Identifying the impacts of policy, economic and social changes on the built environment; specifically focusing on changes to property markets and built form.
  2. Providing students with an understanding of the strengths and limitations of property and spatial data analysis methods and techniques. This will enable them to identify the appropriateness and validity of both their own research and that of others.
  3. Encouraging students to use empirical means to test existing theories of property market behaviours.
  4. Equipping students with the technical skills to gather, integrate, manage, clean, analyse and visualise property data.

This subject works through the process of conceptual understanding and hypothesis generation, followed by the collection, management, analysis and visualisation of related property and spatial data. At each stage both theory, technique and tools are presented as an integrated unit allowing students to understand why an analysis is done, where property data is sourced, what necessary software products are to be used and how analysis will generate visualised results.

Intended learning outcomes

Upon completion of this subject students are expected to:

  • Understand the key conceptual relationships between the impacts of policy, economic and societal changes on property market fundamentals;
  • Answer questions regarding growth and change in urban areas with a data-driven approach;
  • Critique existing property data analyses and reports;
  • Locate and obtain available data for conducting analyses of property markets;
  • Integrate, manage and clean gee-spatial data relating to property markets;
  • Map and visualise the results of property data analysis.

Last updated: 29 May 2017