Name: Social Inquiry and Bayesian Inference: Rethinking Qualitative Research (Strategies for Social Inquiry) (en Inglés)
Price: 154130.00 CLP
Availability: InStock
Author: Fairfield, Tasha ; Charman, Andrew E.
ISBN: 9781108421645

portada Social Inquiry and Bayesian Inference: Rethinking Qualitative Research (Strategies for Social Inquiry) (en Inglés)

Formato

Libro Físico

Autor

Tasha Fairfield

Andrew E. Charman

Editorial

Cambridge University Press

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Dura

Dimensiones

24.4 x 17.0 x 3.7 cm

Peso

1.27 kg.

ISBN13

9781108421645

Categorías

Política y gobierno

Social Inquiry and Bayesian Inference: Rethinking Qualitative Research (Strategies for Social Inquiry) (en Inglés)

Tasha Fairfield (Autor) · Andrew E. Charman (Autor) · Cambridge University Press · Tapa Dura

Libro Físico

$ 154.130

$ 256.880

Ahorras: $ 102.750

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Reseña del libro "Social Inquiry and Bayesian Inference: Rethinking Qualitative Research (Strategies for Social Inquiry) (en Inglés)"

Fairfield and Charman provide a modern, rigorous and intuitive methodology for case-study research to help social scientists and analysts make better inferences from qualitative evidence. The book develops concrete guidelines for conducting inference to best explanation given incomplete information; no previous exposure to Bayesian analysis or specialized mathematical skills are needed. Topics covered include constructing rival hypotheses that are neither too simple nor overly complex, assessing the inferential weight of evidence, counteracting cognitive biases, selecting cases, and iterating between theory development, data collection, and analysis. Extensive worked examples apply Bayesian guidelines, showcasing both exemplars of intuitive Bayesian reasoning and departures from Bayesian principles in published case studies drawn from process-tracing, comparative, and multimethod research. Beyond improving inference and analytic transparency, an overarching goal of this book is to revalue qualitative research and place it on more equal footing with respect to quantitative and experimental traditions by illustrating that Bayesianism provides a universally applicable inferential framework.