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This paper describes a case study of score data analysis for the pre-warning students of a university. The analytical method includes statistical approach and data mining. Through statistical analysis for given pre-warning student score data, the present situation and trend, as well as relevant pre-warning information can be acquired. By associating technique, association rules about the curricula show the dependence and relationship among pre-warning courses. The discovered patterns are helpful for decision making, as well as improvement of the quality of college education in a university.