Analysis of the course contents of statistics at bachelors level in Turkey with data mining techniques

Today with developing technology it is noticed that there is increase in the data quantity and diversity quickly. Depending on the data increase, huge and complicated datasets are formed. Data mining can easily analyze these huge and complicated datasets with data mining methods to search out helpful information.In this thesis; The course contents of the Statistics Department of Çukurova University and the Statistics Departments of other Universities were compared and analyzed using the data mining method. In the findings obtained from the analyzes, the relations of the statistical sections were examined. As a result, it is aimed to obtain the factors that affect the success of statistics departments and the courses that should be taken together in statistics departments by using data mining method. In the analysis of data, clustering analysis, association rules analysis and decision tree analysis were used. The common courses of the statistical departments were examined by cluster analysis. Association rules analysis was used to determine which courses should be taken together in the curriculum of the departments of statistics. Detecting the courses that affect the success of statistical departments was made by decision tree analysis. KNIME and WEKA data mining programs were used for analysis.