Research Information System
4. International Mediterranean Scientific Research Congress, Lefkoşa, Cyprus (Kktc), 15 June 2023, pp.157-158
A cluster is defined as a collection of objects that are brought together or considered to be together
according to one or more of their properties. Cluster analysis techniques are one of the multivariate
statistical methods that are defined as a collection of methods developed to cluster (divide into
homogeneous subgroups) cases (or variables) within the framework of their properties. The
determination of the number of clusters (k) has great importance in clustering analysis. The input data
(variables) and algorithm (methods) are both important issues in the determination of “k” in clustering
analysis. Good clustering is possible in data sets with significant variables and when appropriate
clustering algorithms are used. This study is a study in which the mentioned sensitivities of cluster
analysis are given importance. In this study, the causes of death in Turkey in 2020 by province-based
were analyzed through clustering analysis. The data are taken from the official website of the Turkish
Statistical Institute and analyzed with the SPSS program. Alternative techniques were compared with
each other using reasonable variables to determine the appropriate number of clusters. All findings point
to a two-cluster solution. The province of Istanbul, which is in the first cluster, differs from the rest of
the provinces in the second cluster.