Data Mining for the Social Sciences

An Introduction

Nonfiction, Social & Cultural Studies, Social Science, Demography, Political Science, Politics, Economic Conditions
Cover of the book Data Mining for the Social Sciences by Paul Attewell, David Monaghan, University of California Press
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Author: Paul Attewell, David Monaghan ISBN: 9780520960596
Publisher: University of California Press Publication: April 30, 2015
Imprint: University of California Press Language: English
Author: Paul Attewell, David Monaghan
ISBN: 9780520960596
Publisher: University of California Press
Publication: April 30, 2015
Imprint: University of California Press
Language: English

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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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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