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Designing Social Inquiry: Scientific Inference in Qualitative Research (Englisch) Taschenbuch – 2. Mai 1994


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Produktinformation

  • Taschenbuch: 264 Seiten
  • Verlag: Princeton Univ Pr; Auflage: New. (2. Mai 1994)
  • Sprache: Englisch
  • ISBN-10: 0691034710
  • ISBN-13: 978-0691034713
  • Größe und/oder Gewicht: 1,9 x 15,9 x 23,5 cm
  • Durchschnittliche Kundenbewertung: 4.3 von 5 Sternen  Alle Rezensionen anzeigen (3 Kundenrezensionen)
  • Amazon Bestseller-Rang: Nr. 62.096 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
  • Komplettes Inhaltsverzeichnis ansehen

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Produktbeschreibungen

Pressestimmen

"The book is marked by a very careful building up of all concepts; by clear, vivid writing; and by an excellent use of extended examples from the work of such scholars as Nina Halpern, Atul Kohli, and David Laiting."--Journal of Politics

Synopsis

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.


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THIS BOOK is about research in the social sciences. Lesen Sie die erste Seite
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis
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9 von 9 Kunden fanden die folgende Rezension hilfreich Von xekinai_mia am 19. Februar 2007
Format: Taschenbuch
Das Buch will zeigen, was seriöses qualitativ-sozialwissenschaftliches Arbeiten ausmacht und welche Kriterien und Standards dabei zu beachten sind. Es fokussiert auf Fallstudien und geht von der erfrischenden Prämisse aus, dass gute qualitative Arbeit sich nicht prinzipiell von guter quantitativer unterscheidet. Der (aus historisch nachvollziehbaren Gründen) oft ideologisch aufgeblähte Gegensatz zwischen diesen Forschungstraditionen wird relativiert.

Im ersten Kapitel werden der Wissenschaftsbegriff erläutert, Kriterien für gute Forschung benannt, einige grundsätzliche Empfehlungen für gute Forschungsdesigns gegeben und die Hauptthemen des Buches vorgestellt. Das zweite Kapitel befasst sich mit "Descriptive Inference", d.h. Möglichkeiten und Qualitätskriterien für das Schließen von beobachteten auf nicht beobachtete Tatbestände. Auf die gleiche Weise setzt sich Kapitel 3 mit "Causality and Causal Inference", also dem Ziehen von Kausalschlüssen auseinander. Beide Kapitel präsentieren zunächst eine elaborierte mathematische Definition und ein formales Modell des beschreibenden bzw. kausalen Schließens, bevor sie auf das Handwerkszeug eingehen. Kapitel 4, "Determining What to Observe" formuliert Kriterien für die fundierte Auswahl der zu analysierenden Daten. Kapitel 5 "Understanding What to Avoid" setzt sich mit Möglichkeiten auseinander, Messfehler, Verzerrungen oder die Heranziehung überflüssiger Erklärungsvariablen zu vermeiden. Kapitel 6, "Increasing the Number of Observations", behandelt einen Kerngedanken der Autoren: Forschungsergebnisse werden umso solider, je breiter die Datengrundlage ist.
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2 von 3 Kunden fanden die folgende Rezension hilfreich Von Ein Kunde am 7. August 1998
Format: Taschenbuch
Especially in an election year, the careful and critical examination of public policy and statistical findings is essential. In "Designing Inquiry..." King, Verba and Keohane explain basic statistical and methodological concepts previously only understandable to those studying the advanced social sciences. Concepts such as "endogeneity" and other logical fallacies are explained in language that is easy for the layman to understand, and in enough detail to be a gem for experts in the social sciences. The book explains in simple detail concepts that could be used by anyone to fairly evaluate the results of any study, and does it in a way that anyone can understand. Given the fact that many studies are passed off as "scientific" by journalists, politicians, and special interest groups when, in reality, they are fundamentally flawed, this book offers anyone the opportunity to learn how to critically evaluate studies, and how to reject studies t! hat are often utilized more to fool the voting public and appeal to emotion rather than logic. This book is one of the most significant ones of the decade, and should be read by all wanting to critically participate in a world where the term "scientific study" is often used more as an attempt to convince people of flawed findings rather than logically grounded results.
Sean A. McKitrick
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0 von 1 Kunden fanden die folgende Rezension hilfreich Von A. Manatschal am 16. April 2009
Format: Taschenbuch
Mit zahlreichen wertvollen Richtlinen, wie qualitative Forschung betrieben werden sollte. Die zentrale These des Buches, wonach qualitative und quantitative Forschung dieselbe Inferenz-Logik teilen, hat den Weg für Einsichten geebnet, wie über die Anwendung quantitativer Prinzipien die Präzision qualitativer Forschung verbessert werden kann.
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 16 Rezensionen
33 von 36 Kunden fanden die folgende Rezension hilfreich
This not a stats book 17. Oktober 2005
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Taschenbuch
This is a response to reviewers who think this is a stat book. This book is not meant to serve as a stats textbook (if you want one there are plenty of good ones written by statisticians and econometricians). This book is designed to serve as a guide to research design in social science in terms of developing a question, following systematic research procedures and measurement while using qualitative research methods. In that regard it does not do a great job as they are stuck up with applying simplistic statistical techniques (predominantly regression analysis)to qualitative methodology. As a result the work ends up appearing weak to both the statistically inclined (including myself) and those who use predominantly qualitative methods. Arguably the biggest problems with this work is in their treatment of constant dependent variable designs. This arises from their notion of a "causal effect" that is quite different from what qualitative researchers might see as causality. In statistical terms their notion is correct but when we move towards a qualitative interpretation of the same the concept becomes problematic primarily because it is difficult to discern the appropriate differentation between values of the dependent variable in qualitative work.

Nonetheless, this book should be treated on its own terms for attempting to synthesize quantiative and qualitative research methods. This book started a controversy that continues till this day and did a great job in forcing people to actually think more deeply about their research design and methods.

If you want to study statistics or econometrics forget this book (choose what you want to know about....regression analysis, time-series models, bayesian models....your choice). If you want to study qualitative research well read this book but then read Brady and Collier 2002 and George and Bennett 2004. George and Bennett's work is arguably the best book on research design I have ever read.
32 von 37 Kunden fanden die folgende Rezension hilfreich
Want to Avoid Being Hoodwinked? Here's A Way To Learn! 7. August 1998
Von Ein Kunde - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Especially in an election year, the careful and critical examination of public policy and statistical findings is essential. In "Designing Inquiry..." King, Verba and Keohane explain basic statistical and methodological concepts previously only understandable to those studying the advanced social sciences. Concepts such as "endogeneity" and other logical fallacies are explained in language that is easy for the layman to understand, and in enough detail to be a gem for experts in the social sciences. The book explains in simple detail concepts that could be used by anyone to fairly evaluate the results of any study, and does it in a way that anyone can understand. Given the fact that many studies are passed off as "scientific" by journalists, politicians, and special interest groups when, in reality, they are fundamentally flawed, this book offers anyone the opportunity to learn how to critically evaluate studies, and how to reject studies t! hat are often utilized more to fool the voting public and appeal to emotion rather than logic. This book is one of the most significant ones of the decade, and should be read by all wanting to critically participate in a world where the term "scientific study" is often used more as an attempt to convince people of flawed findings rather than logically grounded results.
Sean A. McKitrick
31 von 36 Kunden fanden die folgende Rezension hilfreich
Contrary to what my colleague from the Netherlands thinks... 5. Juni 2001
Von Michael Vogler - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Hands down, this is one of the best texts of qualitative methodology available for the political scientist. The ideas and arguments made in this volume are very pertinent to study creation. Moreover, King et al. are both willing and able to criticize one of the most common logical fallacies that we find in the literature: the misuse of inference. What my colleague from the Netherlands overlooks is the clear and oft-stated differentiation between correlation and how it applies to THEORIES OF CAUSATION. By not reading the text in a clear way, my colleague has also confused the issue of theory vs. hypothesis as well as the focus of the work on testing hypotheses derived from theories objectively. The mathematical notations used are SPECIFIED as only being applicable in the abstract. In fact, one does not need the math to understand the points made. Moreover, my colleague notes that there are some problems with categorization, despite the fact that King et al acknowledge that if you can't categorize it or find data on it, then you should change your hypotheses and try again. Quite honestly, I question whether or not this gentleman bothered to read the book. I don't see how the points made in this volume could be any clearer. I would recommend this book to anyone seeking an all encompassing approach to qualitative analysis. However, if you are a person that sees little or no value to testing theories or are very polarized in the qualitative vs. quantitative debate, then you are most likely better off reading a good novel than this book.
20 von 23 Kunden fanden die folgende Rezension hilfreich
All the advantages and disadvantages of statistical reasoning applied to qualitative political science 29. Januar 2006
Von Arthur Digbee - Veröffentlicht auf Amazon.com
Format: Taschenbuch
This book takes the basic logic of statistical inference and applies it to qualitative research design in political science. As several reviewers note, it is not a book on statistics, nor indeed does it pretend to be. However, it extends the logic of statistical research design into nonquantitative research.

That much it does very well. By thinking about how to test hypotheses and how to increase variation in a qualitative research design, it has been very influential. Most important, it has sparked extensive criticism, modifying and delineating its claims.

The book has some amusing flaws. Most of the examples come from the authors' colleagues and graduate students at Harvard, which suggests either that good research is not done by people without that connection or that the authors don't read anything written by people who don't have an office down the hall. The two non-quantitative coauthors have both done extensive qualitative research that demonstrably violates the advice given here--both before and after this book. This is evidence that the advice is hard to follow, that they have not read the book, or that good scholars take other factors into consideration when designing research.

The last hypothesis is in fact the right one. There are many factors that go into good research design, and positivistic hypothesis testing provides only a few. Even many of the examples they give are less appropriate than appears at first glance, addressing evidence that goes well beyond what this book's advice would be.

In short, don't rely on this as a bible. Don't believe its claims that all good research must meet these standards. Still, it's a good handbook for what it seeks to accomplish.
2 von 2 Kunden fanden die folgende Rezension hilfreich
must-read before designing research 1. August 2012
Von Enjolras - Veröffentlicht auf Amazon.com
Format: Taschenbuch
There's a veritable industry of books about scientific logic and political science research. Gary King et al's stands out as amongst the most sophisticated. It doesn't dumb science down. It DOES provide good advice about research and how to select cases. The book is also friendly towards qualitative studies and makes an argument that they are useful if done right.

When my colleagues are asked to name ONE book about research methodology to recommend to new graduate students, this book consistently tops the list.
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