Statistics As Principled Argument

Regular price €41.35
A01=Robert P. Abelson
Author_Robert P. Abelson
Category=PBT
comparison
Construct Yield
Data Set
effect
Effect Size Measure
Embarrassing Footnote
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
ESP
Expected Effect Size
experimental design
Expertness Effect
Ganzfeld Studies
hypothesis
Individual Significance Test
inferential statistics
IQ Gain
IQ Score
Magic
Motor Vehicle Fatalities
multiple
Multiple Comparisons Procedure
Null Hypothesis
Null Hypothesis Tests
persuasive statistical communication
probability theory
procedures
Qualitative Interaction
quantitative reasoning
Random Assignment
Random Effects Model
Random Generating Process
Raw Effect Size
research methodology
Risky Shift
scientific argumentation
significance
size
Social Facilitation Effect
standardized
Standardized Effect Size
test
Vice Versa

Product details

  • ISBN 9780805805284
  • Weight: 332g
  • Dimensions: 152 x 229mm
  • Publication Date: 01 Feb 1995
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike.

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.

Particular statistical methods are discussed, 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. It is therefore assumed that the reader has already had some access to elementary statistics. Many examples are included to explain the connection of statistics to substantive claims about real phenomena.