04454nam 2200997 450 991078815230332120230126211141.00-520-28098-90-520-96059-910.1525/9780520960596(CKB)2670000000602040(EBL)1882080(SSID)ssj0001437791(PQKBManifestationID)12536720(PQKBTitleCode)TC0001437791(PQKBWorkID)11373799(PQKB)11120303(MiAaPQ)EBC1882080(DE-B1597)519142(OCoLC)905221641(DE-B1597)9780520960596(Au-PeEL)EBL1882080(CaPaEBR)ebr11033069(CaONFJC)MIL751724(EXLCZ)99267000000060204020150328h20152015 uy 0engur|nu---|u||utxtccrData mining for the social sciences an introduction /Paul Attewell and David B. MonaghanOakland, California :University of California Press,2015.©20151 online resource (265 p.)Description based upon print version of record.0-520-28097-0 1-336-20438-9 Includes bibliographical references and index.Front matter --CONTENTS --ACKNOWLEDGMENTS --1. WHAT IS DATA MINING? --2. CONTRASTS WITH THE CONVENTIONAL STATISTICAL APPROACH --3. SOME GENERAL STRATEGIES USED IN DATA MINING --4. IMPORTANT STAGES IN A DATA MINING PROJECT --5. PREPARING TRAINING AND TEST DATASETS --6. VARIABLE SELECTION TOOLS --7. CREATING NEW VARIABLES --8. EXTRACTING VARIABLES --9. CLASSIFIERS --10. CLASSIFICATION TREES --11. NEURAL NETWORKS --12. CLUSTERING --13. LATENT CLASS ANALYSIS AND MIXTURE MODELS --14. ASSOCIATION RULES --CONCLUSION. Where Next? --BIBLIOGRAPHY --NOTES --INDEXWe 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.Social sciencesData processingSocial sciencesStatistical methodsData mininganalyzing data.bayesian networks.big data.bootstrapping.business analytics.chaid.classification and regression trees.classification trees.confusion matrix.data analysis.data mining.data processing.data scholarship.data science.hardware for data mining.heteroscedasticity.naive bayes.partition trees.permutation tests.scholarly data.social science.social scientists.software for data mining.statistical methods.statistical modeling.studying data.text mining.vif regression.weka.Social sciencesData processing.Social sciencesStatistical methods.Data mining.006.3/12Attewell Paul A.1949-1489068Monaghan David B.1988-MiAaPQMiAaPQMiAaPQBOOK9910788152303321Data mining for the social sciences3709571UNINA