عرض عادي

Data mining for the social sciences : an introduction / Paul Attewell and David B. Monaghan with Darren Kwong.

بواسطة:المساهم (المساهمين):نوع المادة : نصنصالناشر:Oakland, California : University of California Press, 2015الطبعات:First editionوصف:xi, 252 pages : illustrations ; 26 cmنوع المحتوى:
  • text
نوع الوسائط:
  • unmediated
نوع الناقل:
  • volume
تدمك:
  • 9780520280977 (cloth : alk. paper)
  • 0520280970 (cloth : alk. paper)
  • 9780520280984 (pbk. : alk. paper)
  • 0520280989 (pbk. : alk. paper)
الموضوع:تصنيف مكتبة الكونجرس:
  • H61.3 .A88 2015
ملخص:"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.
المقتنيات
نوع المادة المكتبة الحالية رقم الطلب رقم النسخة حالة تاريخ الإستحقاق الباركود
كتاب كتاب UAE Federation Library | مكتبة اتحاد الإمارات General Collection | المجموعات العامة H61.3 .A88 2015 (إستعراض الرف(يفتح أدناه)) C.1 Library Use Only | داخل المكتبة فقط 30020000033073
Browsing UAE Federation Library | مكتبة اتحاد الإمارات shelves, Shelving location: General Collection | المجموعات العامة إغلاق مستعرض الرف(يخفي مستعرض الرف)
H61.295 H36 2007 Handbook of narrative inquiry : mapping a methodology / H61.295 .S29 2013 Duoethnography / H61.295 .S29 2013 Duoethnography / H61.3 .A88 2015 Data mining for the social sciences : an introduction / H61.3 B396 2013 Qualitative data analysis with NVivo / H61.3 B396 2013 Qualitative data analysis with NVivo / H61.3 B3962 2013 Qualitative data analysis : practical strategies /

Includes bibliographical references (pages 252-281) and index.

"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.

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