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Permutation Tests: A Practical Guide to Resampling Methods for Testing Hypotheses
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Catalogue Information
Field name
Details
Dewey Class
519.56
Title
Permutation Tests ([EBook]) : A Practical Guide to Resampling Methods for Testing Hypotheses / by Phillip Good.
Author
Good, Phillip I.
Other name(s)
SpringerLink (Online service)
Publication
New York, NY : Springer , 1994.
Physical Details
X, 228 pages, 9 illus. : online resource.
Series
Springer Series in Statistics
0172-7397
ISBN
9781475723465
Summary Note
Permutation tests permit us to choose the test statistic best suited to the task at hand. This freedom of choice opens up a thousand practical applications, including many which are beyond the reach of conventional parametric sta tistics. Flexible, robust in the face of missing data and violations of assump tions, the permutation test is among the most powerful of statistical proce dures. Through sample size reduction, permutation tests can reduce the costs of experiments and surveys. This text on the application of permutation tests in biology, medicine, science, and engineering may be used as a step-by-step self-guiding reference manual by research workers and as an intermediate text for undergraduates and graduates in statistics and the applied sciences with a first course in statistics and probability under their belts. Research workers in the applied sciences are advised to read through Chapters 1 and 2 once quickly before proceeding to Chapters 3 through 8 which cover the principal applications they are likely to encounter in practice. Chapter 9 is a must for the practitioner, with advice for coping with real life emergencies such as missing or censored data, after-the-fact covariates, and outliers. Chapter 10 uses practical applications in archeology, biology, climatology, education and social science to show the research worker how to develop new permutation statistics to meet the needs of specific applications. The practitioner will find Chapter 10 a source of inspiration as well as a practical guide to the development of new and novel statistics.:
Contents note
1. A Wide Range of Applications -- 2. A Simple Test -- 3. Testing Hypotheses -- 4. Experimental Designs -- 5. Multivariate Analysis -- 6. Categorical Data -- 7. Dependence -- 8. Clustering in Time and Space -- 9. Coping with Disaster -- 10. Which Statistic? Solving the Insolvable -- 11. Which Test Should You Use? -- 12. Publishing Your Results -- 13. Increasing Computational Efficiency -- 14. Theory of Permutation Tests -- Bibliography Part 1: Randomization -- Bibliography Part 2: Supporting -- Bibliography Part 3: Computational Methods -- Bibliography Part 4: Seminal Articles.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-1-4757-2346-5
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Subject References:
Biomathematics
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Mathematical and Computational Biology
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Resampling (Statistics)
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Statistical hypothesis testing
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Statistics
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Statistics for Life Sciences, Medicine, Health Sciences
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Authors:
Good, Phillip I.
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SpringerLink (Online service)
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Series:
Springer Series in Statistics
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Classification:
519.56
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