This volume introduces data mining through case studies of enrollment management. Six case studies employed data mining for solving real-life issues in enrollment yield, retention, transfer-outs, utilization of advanced-placement scores, and predicting graduation rates, among others. The authors furnish a tangible sense of data mining at work. The volume also demonstrates that data mining bears great potential to enhance institutional research. The opening chapter deciphers the similarities and differences between data mining and statistics, debunks the myths surrounding both data mining and traditional statistics, and points out the intrinsic conflict between statistical inference and the emerging need for individual pattern recognition and resulting customized treatment of students - the so-called new reality in applied institutional research.

This is the 131^st volume of New Directions for Institutional Research, a quarterly journal published by Jossey-Bass.

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