Introducing a variety of social science methodologies through an integrated approach, this textbook is applicable to a range of advanced undergraduate and postgraduate social and political science courses, including politics, sociology, communications, business, management and economics.
Introducing a variety of social science methodologies through an integrated approach, this textbook is applicable to a range of advanced undergraduate and postgraduate social and political science courses, including politics, sociology, communications, business, management and economics.
John Gerring is Professor of Government at the University of Texas, Austin. He is the author of several books, including Social Science Methodology: A Unified Framework, 2nd edition (Cambridge, 2012) and Case Study Research: Principles and Practices, 2nd edition (Cambridge, forthcoming, 2017). He is also co-editor of the Cambridge series, Strategies for Social Inquiry.
Inhaltsangabe
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.
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.
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.
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.
Rezensionen
'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
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