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Knowledge Discovery in the Social Sciences

A Data Mining Approach

Xiaoling Shu

ca. 44,99
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University of California Press img Link Publisher

Sozialwissenschaften, Recht, Wirtschaft / Methoden der empirischen und qualitativen Sozialforschung


Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. 

Readers will learn to: 
• appreciate the role of data mining in scientific research 
• develop an understanding of fundamental concepts of data mining and knowledge discovery
• use software to carry out data mining tasks
• select and assess appropriate models to ensure findings are valid and meaningful
• develop basic skills in data preparation, data mining, model selection, and validation
• apply concepts with end-of-chapter exercises and review summaries

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statistical analysis, text mining, data mining, scholarly research, data processing, social science, academic, web mining, anova test, matrix, best fit model, causality, classification, scholarly, academic research, regression, collecting data, scientific study, scientific research, box plot, variables, decision trees, statistics