Data mining for the social sciences : an introduction /

Saved in:
Bibliographic Details
Author / Creator:Attewell, Paul A., 1949- author.
Imprint:Oakland, California : University of California Press, [2015]
Description:xi, 252 pages ; 26 cm
Language:English
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/10393791
Hidden Bibliographic Details
Other authors / contributors:Monaghan, David B., 1988- author.
Kwong, Darren, author.
ISBN:9780520280977
0520280970
9780520280984
0520280989
9780520960596
0520960599
Notes:Includes bibliographical references and index.
Summary:"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.

MARC

LEADER 00000pam a2200000 i 4500
001 10393791
003 ICU
005 20151209141743.3
008 140909s2015 caua b 001 0 eng c
010 |a  2014035276 
019 |a 894745445 
020 |a 9780520280977  |q hardcover ;  |q alkaline paper 
020 |a 0520280970  |q hardcover ;  |q alkaline paper 
020 |a 9780520280984  |q paperback ;  |q alkaline paper 
020 |a 0520280989  |q paperback ;  |q alkaline paper 
020 |z 9780520960596  |q electronic book 
020 |z 0520960599  |q electronic book 
035 |a (OCoLC)894491465  |z (OCoLC)894745445 
040 |a CU-S/DLC  |b eng  |e rda  |c CUS  |d DLC  |d OCLCO  |d OCLCF  |d YDXCP  |d CDX  |d WAU  |d BTCTA  |d BDX  |d N15  |d NLE  |d CHVBK  |d Z@L  |d OCLCQ  |d NhCcYBP 
042 |a pcc 
050 0 0 |a H61.3  |b .A88 2015 
082 0 0 |a 006.3/12  |2 23 
100 1 |a Attewell, Paul A.,  |d 1949-  |e author.  |0 http://id.loc.gov/authorities/names/n82214112  |1 http://viaf.org/viaf/59100058 
245 1 0 |a Data mining for the social sciences :  |b an introduction /  |c Paul Attewell and David B. Monaghan, with Darren Kwong. 
264 1 |a Oakland, California :  |b University of California Press,  |c [2015] 
300 |a xi, 252 pages ;  |c 26 cm 
336 |a text  |b txt  |2 rdacontent  |0 http://id.loc.gov/vocabulary/contentTypes/txt 
337 |a unmediated  |b n  |2 rdamedia  |0 http://id.loc.gov/vocabulary/mediaTypes/n 
338 |a volume  |b nc  |2 rdacarrier  |0 http://id.loc.gov/vocabulary/carriers/nc 
504 |a Includes bibliographical references and index. 
505 0 |a What is data mining? -- Contrasts with the conventional statistical approach -- Some general strategies used in data mining -- Important stages in a data mining project -- Preparing training and test datasets -- Variable selection tools -- Creating new variables using binning and trees -- Extracting variables -- Classifiers -- Classification trees -- Neural networks -- Clustering -- Latent class analysis and mixture models -- Association rules. 
520 |a "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. 
650 0 |a Social sciences  |x Data processing.  |0 http://id.loc.gov/authorities/subjects/sh85124007 
650 0 |a Social sciences  |x Statistical methods.  |0 http://id.loc.gov/authorities/subjects/sh85124018 
650 0 |a Data mining.  |0 http://id.loc.gov/authorities/subjects/sh97002073 
650 7 |a Data mining.  |2 fast  |0 (OCoLC)fst00887946 
650 7 |a Social sciences  |x Data processing.  |2 fast  |0 (OCoLC)fst01122901 
650 7 |a Social sciences  |x Statistical methods.  |2 fast  |0 (OCoLC)fst01122983 
650 7 |a Sozialwissenschaften.  |0 (DE-588)4055916-6  |2 gnd 
650 7 |a Data Mining.  |0 (DE-588)4428654-5  |2 gnd 
700 1 |a Monaghan, David B.,  |d 1988-  |e author.  |0 http://id.loc.gov/authorities/names/no2014117127  |1 http://viaf.org/viaf/310631454 
700 1 |a Kwong, Darren,  |e author.  |0 http://id.loc.gov/authorities/names/no2015071306  |1 http://viaf.org/viaf/316001242 
903 |a HeVa 
929 |a cat 
999 f f |i 319b101c-40e5-535f-8735-f76b89a32f14  |s 3caef5f0-2bd1-576c-90bf-0b3d1a6d84e2 
928 |t Library of Congress classification  |a H61.3.A88 2015  |l JRL  |c JRL-Gen  |i 8567665 
927 |t Library of Congress classification  |a H61.3.A88 2015  |l JRL  |c JRL-Gen  |e CARL  |b 111897851  |i 9524641