Date of Publication
10-13-2010
Document Type
Master's Thesis
Degree Name
Master of Science in Computer Science
Subject Categories
Computer Sciences
College
College of Computer Studies
Department/Unit
Computer Science
Thesis Adviser
Nelson Marcos
Defense Panel Chair
Kai Shan L. Fernandez
Defense Panel Member
Nelson Marcos
Shirley B. Chu
Abstract/Summary
This research is about developing a system using regression modelling to create poverty models and combine with spatial analysis that can simulate poverty reduction strategies. Statistical Package for the Social Sciences (SPSS) was used to generate the poverty models applying regression modeling on Community-Based Monitoring System (CBMS) data with 14 poverty indicators. Simulations were done using the data from Pasay Metro Manila in order to see the effects of variables to poverty models. Results were presented in numerical and graphical form using maps. The results were able to show meaningful results that can assist the officials in setting priorities and identifying beneficiaries when planning their programs.
Abstract Format
html
Language
English
Format
Electronic File Format
MS WORD
Accession Number
TG04878; CDTG004878
Shelf Location
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
Physical Description
x, 97 leaves ; 28 cm.
Keywords
Poverty--Simulation methods; Regression analysis; Spatial analysis (Statistics)
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Recommended Citation
Tan, K. R. (2010). Simulating poverty reduction strategy with the use of regression modeling and spatial analysis. Retrieved from https://animorepository.dlsu.edu.ph/etd_masteral/3998
