Original title: Bayesian Networks for the Analysis of Subjective Well-Being
Authors: Švorc, Jan ; Vomlel, Jiří
Document type: Papers
Conference/Event: Czech-Japan Seminar on Data Analysis and Decision Making 2019 /22./, Bojkovice (CZ), 20190925
Year: 2019
Language: eng
Abstract: We use Bayesian Networks to model the influence of diverse socio-economic factors on subjective well-being and their interrelations. The classical statistical analysis aims at finding significant explanatory variables, while Bayesian Networks can also help sociologists to explain and visualize the problem in its complexity. Using Bayesian Networks the sociologists may get a deeper insight into the interplay of all measured factors and their influence on the variable of a special interest. In the paper we present several Bayesian Network models -- each being optimal from a different perspective. We show how important it is to pay a special attention to a local structure of conditional probability tables. Finally, we present results of an experimental evaluation of the suggested approaches based on real data from a large international survey. We believe that the suggested approach is well applicable to other sociological problems and that Bayesian Networks represent a new valuable tool for sociological research.
Keywords: Bayesian networks; Subjective well-being
Project no.: GA19-04579S (CEP), GA17-08182S (CEP)
Funding provider: GA ČR, GA ČR
Host item entry: Proceedings of the 22nd Czech-Japan Seminar on Data Analysis and Decision Making (CJS’19), ISBN 978-80-7378-400-3

Institution: Institute of Information Theory and Automation AS ČR (web)
Document availability information: Fulltext is available at external website.
External URL: http://library.utia.cas.cz/separaty/2019/MTR/svorc-0509113.pdf
Original record: http://hdl.handle.net/11104/0300870

Permalink: http://www.nusl.cz/ntk/nusl-407865


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Research > Institutes ASCR > Institute of Information Theory and Automation
Conference materials > Papers