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Designing Social Inquiry: Scientific Inference in Qualitative Research
Contributor(s): King, Gary (Author), Keohane, Robert O. (Author), Verba, Sidney (Author)
ISBN: 0691034710     ISBN-13: 9780691034713
Publisher: Princeton University Press
OUR PRICE:   $36.75  
Product Type: Paperback - Other Formats
Published: May 1994
* Not available - Not in print at this time *Annotation: Designing Social inquiry focuses on improving qualitative research, where numerical measurement is either impossible or undesirable. What are the right questions to ask? How should you define and make inferences about casual effects? How can you avoid bias? How many cases do you need, and how should they be selected? What are the consequences of unavoidable problems in qualitative research, such as measurement error, incomplete information, or omitted variables? What are proper ways to estimate and report the uncertainty of your conclusions? How would you know if you were wrong?
Additional Information
BISAC Categories:
- Social Science | Research
- Social Science | Sociology - General
- Political Science
Dewey: 300.72
LCCN: 93039283
Physical Information: 0.6" H x 6.1" W x 9.1" (0.80 lbs) 264 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research performed in this field. These leading scholars, each representing diverse academic traditions, have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. Their book demonstrates that the same logic of inference underlies both good quantitative and good qualitative research designs, and their approach applies equally to each.

Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and uncertainty of empirical inferences, discovering causal effects, and generally improving qualitative research. Among the specific topics they address are interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed. The unified logic of inference that this book explicates will be enormously useful to qualitative researchers of all traditions and substantive fields.