Description
Book SynopsisThis 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,
Trade Review'An excellent guide to the main approaches and issues of social science research design. It offers a clear guide through the thicket of terms and concepts with effective use of examples. A valuable work for students of any level.' Kenneth Benoit, London School of Economics and Political Science
'Rich, compelling, engaging, passionate and in crystal-clear style. Gerring and Christenson have done an excellent job in promoting an integrated and pluralist vision of methodology and research design.' Martino Maggetti, University of Lausanne, Switzerland
Table of ContentsPreface; 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.
