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Designing Social Inquiry: Scientific Inference in Qualitative Research

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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.

300 pages, Paperback

First published January 1, 1994

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Gary King

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Displaying 1 - 25 of 25 reviews
89 reviews2 followers
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July 30, 2011
Very well organized approach to both qualitative and quantitative studies in the social sciences. KKV explain in depth and justify what, realistically, many of us do unconciously (though incompletely) in making causal inferences. An invaluable read for anyone in the social sciences, and particularly those interested in a case-study approach to a given problem. KKV manage to explain much of their method in simple, readable terms, avoiding much of the jargon so commonly associated with methodological theory. Overall, I rate this book very highly for anyone interested in any type of causal inference, but in particular for those in the social sciences.
18 reviews
January 20, 2009
yes my books are getting drier but as I PhD student I no longer choose what I read

This is the book that qualitative researchers love to hate
221 reviews
March 20, 2023
This selection was partly preparation for a class on research methods that I currently teach. I have a number of students who lean on a qualitative approach in their research topics and I wanted to revisit this text to determine how to translate some key research ideas, such as multicollinearity, into qualitative research designs. This book has a wealth of good advice on how to think about inference in general terms and some useful elements for qualitative researchers particularly. I found the guidance it gives on how many units are enough in your qualitative study particularly useful and a framework I plan on presenting as part of my course. If you are planning on masters or Ph.D. studies, this is a really helpful book that is well-written and contains a lot of practical advice. Wouldn't recommend anyone else reading it as the subject matter is rather dry and specific.
Profile Image for Will.
1,750 reviews64 followers
February 3, 2016
KKV's approach to qualitative research is based on the assertions that the causal inference used for both qualitative and quantitative approaches to research design. The book outlays how to construct a research design, though it is largely hostile to single-case study analysis, due to the fact that it relies on causal inference through observing correlation. As such, the solutions KKV provide to bias and inefficiency are largely reliant on increasing the number of observations. The key purpose of this is to seek an increased number of observable implications (observations we would expect to see if our hypothesis were correct). Two key assumptions they assert as being necessary (in both Large and Small N studies) are unit homogeneity (that the two cases are the same apart from the causal effect of the hypothesized value of the explanatory values) as well as conditional dependence (the assumption that values are assigned to explanatory variables independently of the values taken by the dependent variable).
Profile Image for Anna Stevens.
16 reviews
March 18, 2020
Pretty helpful in designing my M.A. dissertation research proposal - would recommend to academics
Profile Image for Reid.
25 reviews6 followers
January 29, 2023
Adequate review of social science research methodology issues and phenomena geared towards qualitative researchers who don't like using formal quantitative procedures, with an emphasis on the fields of political science and sociology.

Crucially, the text's authors posit that a single logic of inference founded on statistical norms guides both quantitative and qualitative research, and in practice, that qualitative methods should only be undertaken as "last resort", when quantitative methods have been exhausted.
Profile Image for Juan Manuel Cafferata.
83 reviews13 followers
March 31, 2022
O sea es un Manual. Como principio te dice "trata de explicar lo más que puedas con la teoría más simple posible usando la mayor cantidad de casos empíricos para contrastar". Pero bueno si no podes, te tira tips para manejarte. En algunos casos bastante turbios. Pero es ciencias sociales, no podemos pedir tanto.
Profile Image for J.R..
255 reviews3 followers
September 6, 2023
Very useful techniques and explanations of trapping for designing qualitative research. Describes how inference, either explanatory or descriptive, is the ultimate goal of social sciences and why that can be so difficult.
Profile Image for Xueqi Sun.
31 reviews3 followers
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January 26, 2025
i guess Randall prepared his TOK methodology class based on this book. nostalgic of Extended Essay
9 reviews
August 4, 2020
Generally a comprehensive and thought provoking book on quantitative and qualitative methodologies, with an implicit priority bestowed to quantitative over qualitative. Though the authors claim to reconcile the contrasting tension between qualitative and quantitative methods, after all it seems a rather disdainful urge compelling the rigid consistency to quantitative ways of conducting social inquiries. KKV’s DSI is a classic and must read for social science students and scholars, nevertheless it is somewhat flawed due to its rough conflation of these two internally distinct methodologies.
Profile Image for Arys Aditya.
Author 7 books17 followers
June 4, 2013
Ah, sayang sekali, buku sekuat ini sama sekali belum ada yang meneruskannya lewat ulasan. Sementara saya sendiri telah kehilangan file ebook-nya.
Buku ini, di ingatan saya, mengulas tuntas beserta contoh-contoh kasus tentang sekian alat analisis dalam penelitian sosial, perdebatan paradigma antara kualitatif-kuantitatif, dan model-model penelitian yang bisa dipakai atau dikaji ulang.
Buku ini juga luar biasa karena beberapa kali saya menemukan banyak orang mengkritiknya dengan keras, yang menandakan bahwa buku ini memang penting dan berharga. Terutama jika anda peneliti atau periset yang bergerak di alam sosial.
Profile Image for Laura.
18 reviews1 follower
July 21, 2009
So far I am in love with this book. Finally someone is making an excellent case for the union of qualitative and quantitative research!
Profile Image for Brian.
9 reviews
March 22, 2014
Good technical breakdown of the subject, it will serve me as a good baseline and reference.
1 review
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December 19, 2015
To know different stage of conducting research
This entire review has been hidden because of spoilers.
309 reviews2 followers
May 5, 2024
Sharp insights into how research should be conducted.
Displaying 1 - 25 of 25 reviews

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