Normal view MARC view ISBD view

Designing social inquiry : scientific inference in qualitative research / Gary King, Robert O. Keohane, Sidney Verba.

By: King, Gary, 1958- [author].
Contributor(s): Keohane, Robert O., (Robert Owen), 1941- | Verba, Sidney.
Material type: materialTypeLabelBookSeries: Princeton paperbacks.Publisher: Princeton, N.J. : Princeton University Press, 1994Copyright date: ©1994Description: xi, 247 pages : illustrations ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 0691034702 (cloth : alk. paper); 9780691034706 (cloth : alk. paper); 0691034710 (pbk. : alk. paper); 9780691034713 (pbk. : alk. paper).Other title: Scientific inference in qualitative research.Subject(s): Social sciences -- Methodology | Social sciences -- Research | Inference | Qualitative research
Contents:
The Science in Social Science -- Descriptive Inference -- Causality and Causal Inference -- Determining What to Observe -- Understanding What to Avoid -- Increasing the Number of Observations.
Summary: 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. -- Publisher description.
Tags from this library: No tags from this library for this title. Log in to add tags.
    average rating: 0.0 (0 votes)
Item type Current location Collection Call number Status Date due Barcode
Book Book Merkez Kütüphane
Genel Koleksiyon / Main Collection
Genel Koleksiyon H61 .K56 1994 (Browse shelf) Available 0060302

Includes bibliographical references (p. [231]-238) and index.

The Science in Social Science -- Descriptive Inference -- Causality and Causal Inference -- Determining What to Observe -- Understanding What to Avoid -- Increasing the Number of Observations.

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. -- Publisher description.

This software was implemented, installed by Devinim Software Training Consulting .