000 02398nam a2200241 4500
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008 250401b |||||||| |||| 00| 0 eng d
020 _a9780691199436
037 _cTextual
040 _aRTL
_cRTL
084 _aY:(D6,9(B) R3
_qRTL
100 _aLlaudet, Elena
_9751663
245 _aData Analysis for Social Science: a friendly and practical introduction
260 _aPrinceton and Oxford
_bPrinceton University Press
_c2023
300 _axii, 238p.
_bIncludes index
520 _aData analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"-- "An ideal textbook for an introductory course on quantitative methods for social scientistsData Analysis for Social Science provides a friendly introduction to the statistical concepts and programming skills needed to conduct and evaluate social scientific studies.
650 _aSocial sciences - Data processing
_9751664
650 _aComputers data analytics
_9751665
650 _aStatistical mathematics
_9751666
650 _aSocial sciences - Methodology
_9643438
700 _aImai, Kosuke
_eCo- author
_9725581
942 _2CC
_n0
_cTB
_hY:(D6,9(B) R3
999 _c1308321
_d1308321