Applied Social Science Methodology : An Introductory Guide

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Applied Social Science Methodology : An Introductory Guide

  • 著者名:Gerring, John/Christenson, Dino
  • 価格 ¥5,676 (本体¥5,160)
  • Cambridge University Press(2017/04/24発売)
  • たんぽぽ揺れる!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~4/12)
  • ポイント 1,530pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9781107071476
  • eISBN:9781108116176

ファイル: /

Description

This textbook provides a clear, concise, and comprehensive introduction to methodological issues encountered by the various social science disciplines. It emphasizes applications, with detailed examples, so that readers can put these methods to work in their research. Within a unified framework, John Gerring and Dino Christenson integrate a variety of methods - descriptive and causal, observational and experimental, qualitative and quantitative. The text covers a wide range of topics including research design, data-gathering techniques, statistics, theoretical frameworks, and social science writing. It is designed both for those attempting to make sense of social science, as well as those aiming to conduct original research. The text is accompanied by online practice questions, exercises, examples, and additional resources, including related readings and websites. An essential resource for undergraduate and postgraduate programs in communications, criminal justice, economics, business, finance, management, education, environmental policy, international development, law, political science, public health, public policy, social work, sociology, and urban planning.

Table of Contents

Preface; Part I. Building Blocks: 1. A unified framework; 2. Arguments; 3. Concepts and measures; 4. Analyses; Part II. Causality: 5. Causal frameworks; 6. Causal hypotheses and analyses; 7. Experimental designs; 8. Large-N observational designs; 9. Case study designs; 10. Diverse tools of causal inference; Part III. Process and Presentation: 11. Reading and reviewing; 12. Brainstorming; 13. Data gathering; 14. Writing; 15. Speaking; 16. Ethics; Part IV. Statistics: 17. Data management; 18. Univariate statistics; 19. Probability distributions; 20. Statistical inference; 21. Bivariate statistics; 22. Regression; 23. Causal inference; 24. Appendix; References; Index.

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