Open AccessComparative Performance of Three Methods to Classify Smokers Data
Author(s) -
Amenah AL-Najafi
Publication year - 2021
Publication title -
österreichische zeitschrift für statistik
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.342
H-Index - 9
ISSN - 1026-597X
DOI - 10.17713/ajs.v50i3.1013
Subject(s) - christian ministry , environmental health , cluster analysis , consumption (sociology) , psychology , medicine , computer science , political science , sociology , artificial intelligence , social science , law
Since recently tobacco epidemic is one of the most important health hazards that face Iraqi individuals and communities in spite of the large information supported by the Iraqi Ministry of Health and the available statistics that link smoking with many life threatening illnesses to human. Tobacco consumption rates are increasing nowadays among university students. Iraqi Ministry of Health confirmed the need to take a serious action to support research that examines the tobacco epidemic among students, in an attempt to find the causes and the appropriate solutions.It is, therefore, our main objective is to investigate the student smokers from the University of Kufa in Iraq. The research attempted to study the behaviour of smokers using questionnaires. The performance of Latent Classes (LC) is evaluated by attempting to classify the student smokers and then compared it to two clustering methods namely K-means and Two-Step method.