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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.
The last half century has seen a dramatic expansion in access to
primary, secondary, and higher education in many nations around the
world. Educational expansion is desirable for a country's economy,
beneficial for educated individuals themselves, and is also a
strategy for greater social harmony. But has greater access to
education reduced or exacerbated social inequality? Who are the
winners and the losers in the scramble for educational advantage?
The last half century has seen a dramatic expansion in access to
primary, secondary, and higher education in many nations around the
world. Educational expansion is desirable for a country's economy,
beneficial for educated individuals themselves, and is also a
strategy for greater social harmony. But has greater access to
education reduced or exacerbated social inequality? Who are the
winners and the losers in the scramble for educational advantage?
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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