Analysis of world values survey using data mining

Amount of numerical data constantly increases, and there appears a problem of efficient analysis of these data. One must explore the meaningful information, correlation and rules, which gives a possibility to guess about future, out of this huge amount of raw data flow. However, there has been a necessity of automatically analysis of such kind of data in huge amount, which cannot be detected by eyes and cannot be analysed manually, by computer technology and programmes. It is called Data Mining. Association rules used in Data Mining enable to make guesses for future by exploring the objects and correlations between those objects that move altogether in the field of data. Scanning database, applying the methods of integration and pruning, and exploring the association relation between the objects with the help of support value generate the fundamental of algorithm. First, models and techniques used for data mining will be pointed out in this study. Association rules and algorithms that are the models of data mining will be examined in detailed. Data of World Values Survey was examined in practice section of the dissertation. The survey questions and answers determined by Turkey and chosen countries were specified in accordance with Association Rules a Priori Algorithm. Consequently, the purpose is to determine both the current situation of Turkey and its position among chosen countries with the data gained.