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Conference Paper (international conference)

Bayesian Networks for the Analysis of Subjective Well-Being

Švorc Jan, Vomlel Jiří

: Proceedings of the 22nd Czech-Japan Seminar on Data Analysis and Decision Making (CJS’19), p. 175-188 , Eds: Inuiguchi Masahiro, Jiroušek Radim, Kratochvíl Václav

: Czech-Japan Seminar on Data Analysis and Decision Making 2019 /22./, (Bojkovice, CZ, 20190925)

: GA19-04579S, GA ČR, GA17-08182S, GA ČR

: Bayesian networks, Subjective well-being

: http://library.utia.cas.cz/separaty/2019/MTR/svorc-0509113.pdf

(eng): 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.

: BA

: 50403