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Pregled bibliografske jedinice broj: 795416

Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach


Žmuk, Berislav
Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach // Croatian Review of Economic, Business and Social Statistics, 1 (2015), 1-2; 42-54 (podatak o recenziji nije dostupan, članak, znanstveni)


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Naslov
Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach

Autori
Žmuk, Berislav

Izvornik
Croatian Review of Economic, Business and Social Statistics (1849-8531) 1 (2015), 1-2; 42-54

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
quality of life indicators; Ward’s method; outlier detection; European countries; analysis of variance (ANOVA)

Sažetak
The average expected duration of human life is rising because of different reasons. On the other hand, not only the duration, but the quality of life level is important also. The higher quality of life level is, the citizens’ happiness and satisfaction levels are higher which has positive impact on the development and operating of an economy. The goal of this paper is to identify groups of European countries, using statistical hierarchical cluster analysis, by using quality of life indicators and to compare their differences in quality of life levels. The quality of life is measured by using seven different indicators. The conducted statistical hierarchical cluster analysis is based on the Ward’s method, as a clustering method, and squared Euclidean distances, as a measure of clustering distances. The results of statistical hierarchical cluster analysis enabled recognizing of three different groups of European countries: old European Union member states, new European Union member states, and non-European Union member states. The analysis has revealed that the old European Union member states seem to have in average higher quality of life level than the new European Union member states. Furthermore, the European Union member states seem to have in average higher quality of live level than non-European Union member states. The results indicate that quality of life levels and economic development levels are connected.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija



POVEZANOST RADA


Ustanove:
Ekonomski fakultet, Zagreb

Profili:

Avatar Url Berislav Žmuk (autor)


Citiraj ovu publikaciju

Žmuk, Berislav
Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach // Croatian Review of Economic, Business and Social Statistics, 1 (2015), 1-2; 42-54 (podatak o recenziji nije dostupan, članak, znanstveni)
Žmuk, B. (2015) Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach. Croatian Review of Economic, Business and Social Statistics, 1 (1-2), 42-54.
@article{article, author = {\v{Z}muk, B.}, year = {2015}, pages = {42-54}, keywords = {quality of life indicators, Ward’s method, outlier detection, European countries, analysis of variance (ANOVA)}, journal = {Croatian Review of Economic, Business and Social Statistics}, volume = {1}, number = {1-2}, issn = {1849-8531}, title = {Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach}, keyword = {quality of life indicators, Ward’s method, outlier detection, European countries, analysis of variance (ANOVA)} }
@article{article, author = {\v{Z}muk, B.}, year = {2015}, pages = {42-54}, keywords = {quality of life indicators, Ward’s method, outlier detection, European countries, analysis of variance (ANOVA)}, journal = {Croatian Review of Economic, Business and Social Statistics}, volume = {1}, number = {1-2}, issn = {1849-8531}, title = {Quality of life indicators in selected European countries: Statistical hierarchical cluster analysis approach}, keyword = {quality of life indicators, Ward’s method, outlier detection, European countries, analysis of variance (ANOVA)} }




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