Visual sensitivity analysis : applied to real estate predication system

Da'ana, M

Visual sensitivity analysis : applied to real estate predication system

Da'ana, M

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Publication Type:: Thesis
Issue Date:: 2014

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Field	Value	Language
dc.contributor.author	Da'ana, M
dc.date.accessioned	2014-03-25T01:21:19Z
dc.date.available	2014-03-25T01:21:19Z
dc.date.issued	2014
dc.identifier.uri	http://hdl.handle.net/10453/24187
dc.description	University of Technology, Sydney. Faculty of Engineering and Information Technology.	en_US
dc.description.abstract	Sensitivity analysis is the science studies the impact of independent variables on the dependant variable in the studied model, in addition to investigating relationships between those variables. Sensitivity analysis is a prevalent group of techniques and approaches has proven its feasibility in wide range of disciplines. However, the traditional sensitivity analysis methods have the common weakness of user interaction absence. Furthermore; each sensitivity analysis method has its own level of difficulty which is an obstacle for a non-expert user to use or even to interpret the results if the analysis is conducted using a software like SPSS. Recently, visualizations are being used to present data efficiently in terms of assisting human visual perception and reducing cognition effort. These visualization techniques when integrated with interaction will facilitate data manipulation and exploration. This study integrates sensitivity analysis with interactive visualization into a prediction system that allows non-expert users to analyse and understand the real estate data through the visualization and direct visual interactions, which hide the complexity of the sensitivity analysis algorithms. We take advantage of the visualization that amplifies cognition in dealing with abstract data. As shown in the outcome, the user can use the sensitivity analysis method used in this system interactively setting his/her preferences for the property via the visualization without any prerequisite of sensitivity analysis knowledge. The use of scatter plots, one of sensitivity analysis methods, is used in studying the relationships between the predictors and the response variables to decide whether variable transformation is needed or not. Additionally, scatter plots are used to summarize all analyses conducted.	en_US
dc.format	Thesis (MSc)	en_US
dc.language.iso	en	en_US
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/24187/2/02whole.pdf
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	au.edu.uts.lib/ppc
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Visual sensitivity analysis : applied to real estate predication system	en_US
dc.type	Thesis
utslib.copyright.status	open_access

Abstract:

Sensitivity analysis is the science studies the impact of independent variables on the dependant variable in the studied model, in addition to investigating relationships between those variables. Sensitivity analysis is a prevalent group of techniques and approaches has proven its feasibility in wide range of disciplines. However, the traditional sensitivity analysis methods have the common weakness of user interaction absence. Furthermore; each sensitivity analysis method has its own level of difficulty which is an obstacle for a non-expert user to use or even to interpret the results if the analysis is conducted using a software like SPSS. Recently, visualizations are being used to present data efficiently in terms of assisting human visual perception and reducing cognition effort. These visualization techniques when integrated with interaction will facilitate data manipulation and exploration. This study integrates sensitivity analysis with interactive visualization into a prediction system that allows non-expert users to analyse and understand the real estate data through the visualization and direct visual interactions, which hide the complexity of the sensitivity analysis algorithms. We take advantage of the visualization that amplifies cognition in dealing with abstract data. As shown in the outcome, the user can use the sensitivity analysis method used in this system interactively setting his/her preferences for the property via the visualization without any prerequisite of sensitivity analysis knowledge. The use of scatter plots, one of sensitivity analysis methods, is used in studying the relationships between the predictors and the response variables to decide whether variable transformation is needed or not. Additionally, scatter plots are used to summarize all analyses conducted.

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http://hdl.handle.net/10453/24187