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Data Mining for the Social Sciences

An Introduction

Paul Attewell, David Monaghan

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University of California Press img Link Publisher

Geisteswissenschaften, Kunst, Musik / Pädagogik

Beschreibung



We live in a world of big data: the amount of information collected on human behavior each day is staggering, and exponentially greater than at any time in the past. Additionally, powerful algorithms are capable of churning through seas of data to uncover patterns. Providing a simple and accessible introduction to data mining, Paul Attewell and David B. Monaghan discuss how data mining substantially differs from conventional statistical modeling familiar to most social scientists. The authors also empower social scientists to tap into these new resources and incorporate data mining methodologies in their analytical toolkits. Data Mining for the Social Sciences demystifies the process by describing the diverse set of techniques available, discussing the strengths and weaknesses of various approaches, and giving practical demonstrations of how to carry out analyses using tools in various statistical software packages.

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Schlagwörter

statistical methods, data mining, permutation tests, statistical modeling, business analytics, bayesian networks, data science, classification trees, partition trees, software for data mining, heteroscedasticity, social scientists, scholarly data, data scholarship, naive bayes, analyzing data, chaid, classification and regression trees, bootstrapping, big data, studying data, data analysis, confusion matrix, data processing, vif regression, hardware for data mining, social science, weka, text mining