Inbunden, Engelska, 2025
Statistics as Principled Argument
Del i serien Psychology Press & Routledge Classic Editions
2489 kr
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Beskrivning
In Statistics as Principled Argument, first published in 1995, Robert P. Abelson exposes the often-overlooked problems in quantitative data interpretation, and the challenge of presenting the data in terms of a coherent narrative about one's research. This classic edition offers a new introduction which views Abelson's work through a contemporary lens, highlighting how his teachings remain vitally relevant today.The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative evidence, using a form of principled rhetoric. Five criteria, described by the acronym MAGIC (magnitude, articulation, generality, interestingness, and credibility) are proposed as crucial features of a persuasive, principled argument. Statistical methods are discussed, but with minimum use of formulas and heavy data sets. The ideas throughout the book revolve around elementary probability theory, t-tests, and simple issues of research design. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.This remarkably engaging read is filled with fascinating real-life (and real research) examples rather than simply recipes for analysis. Abelson’s insights generate true interest for beginning graduate students and seasoned researchers alike, and will be invaluable to students, scholars, researchers, and practitioners who use statistics within their research.
Produktinformation
- Utgivningsdatum: 2025-11-03
- Mått: 152 x 229 x 19 mm
- Vikt: 610 g
- Format: Inbunden
- Språk: Engelska
- Serie: Psychology Press & Routledge Classic Editions
- Antal sidor: 224
- Förlag: Taylor & Francis Ltd
- ISBN: 9781041020998
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Robert P. Abelson was a professor in the psychology and political science departments at Yale University. He made foundational contributions to social psychology, political psychology, and cognitive science, as well as important contributions to statistics.
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