Data mining is a process of discovering new relationships, patterns and trends from
large databases. In this process many statistical methods can be used. Two of these
methods are Bayesian Networks and association analysis. Bayesian Networks are used
to encode probabilistic relationships among random variables and they combine data
information and experts knowledge about data [1]. In the literature, many learning
algorithms have been proposed to build Bayesian Networks. They can also be built
according to association analysis results [2]. Association analysis is used to extract
surprising and useful patterns from large databases. However, association analysis
algorithms generate many patterns even if the data set is very small. Therefore, these
patterns should be eliminated with respect to their interestingness by using objective
and subjective interestingness measures. Subjective measures can be established by
means of Bayesian Networks. In this study, these two methods are used together to
analyze Demographic and Health Survey (DHS) 2008 data of Turkey.