Statistics As Principled Argument 1st edition By Robert Abelson – Ebook PDF Instant Download/Delivery: 0805805284 , 9780805805284
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ISBN 10: 0805805284
ISBN 13: 9780805805284
Author: Robert Abelson
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.
Statistics As Principled Argument 1st Table of contents:
1 Making Claims With Statistics
Misunderstandings of Statistics
Claims Made with Statistics: Comparison and Explanation
Language and Limitations of Null Hypothesis Tests
Persuasive Arguments: the Magic Criteria
Style and Convention
The Bottom Line
2 Elementary Arguments and the Role of Chance
Random Generating Processes
Random Sampling Processes
Summary
3 Magnitude of Effects
Probability Measures
Effect Sizes
Confidence Limits
4 Styles of Rhetoric
Brash, Stuffy, Liberal, and Conservative Styles
One-Tailed, Two-Tailed, and Lopsided Tests
Alternative Tests Applied to the Same Data Set
Defective Observations
Multiple Tests Within the Same Data Set
Stating and Interpreting p Values
In the Last Analysis
5 On Suspecting Fishiness
Strange Distributions of Observations
The Occurrence of Impossible Scores
Strange Test Statistics
Inconsistencies Between Parallel Statistics
Too Much Consistency in Parallel Statistics
A Cautionary Note on the Detection of Fishiness
6 Articulation of Results: Ticks and Buts
Ticks and Buts
Ticks and the Evolution of Knowledge
Comparisons of Pairs of Means
Reframing Results for Better Articulation
Multiple Comparisons
Contrasts
More Than One Dependent Variable
Further Remarks
7 Generality of Effects
The Nature of Generality
Treatment-by-Context Interactions within Studies
Generality Across Studies: Meta-Analysis
Generality Across and Within Studies: A Parallel
Final Caveat
8 Interestingness of Argument
Can Statistics be Interesting?
Theoretical Interest
Surprisingness
Importance
9 Credibility of Argument
Why Research Claims are Disbelieved
The Structure of Debates on Disbelieved Claims
Methodological Artifacts
The Influence of Criticism on Methodology
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