Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package. Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Using examples from published work, the authors demonstrate how to make the most of QCA’s wide-ranging capabilities for the reader’s own purposes. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
1.Loading Neccessary Packages.- 2. Reading Data into R.- 3. Testing for Neccessity.- 4. Testing for Sufficiency 5.- Sufficiency: Parameters of Fit 6.- Plotting Results
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Phatpocket Limited, Waltham Abbey, HERTS, Regno Unito
Condizione: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Codice articolo Z1-A-017-02494
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package. Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Using examples from published work, the authors demonstrate how to make the most of QCA's wide-ranging capabilities for the reader's own purposes. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health. 116 pp. Englisch. Codice articolo 9781461445838
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 116. Codice articolo 2658591524
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Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand pp. 116 20 Illus. Codice articolo 50968315
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Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 2013 edition. 112 pages. 9.37x0.31x6.14 inches. In Stock. Codice articolo x-1461445833
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Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND pp. 116. Codice articolo 1858591534
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