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Resampling methods : a practical guide to data analysis /

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"Most introductory statistics books ignore or give little attention to resampling methods, and thus another generation learns the less than optimal methods of statistical analysis. Good attempts to remedy this situation by writing an introductory text that focuses on resampling methods, and he...

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Bibliographic Details
Main Author: Good, Phillip I.
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Boston : Birkhäuser, [1999]
Subjects:
Resampling (Statistics)
Statistische analyse.
Rééchantillonnage (statistique)
Resampling.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1. Descriptive Statistics
  • 2. Cause and Effect
  • 3. Testing Hypotheses
  • 4. When the Distribution Is Known
  • 5. Estimation
  • 6. Power of a Test
  • 7. Categorical Data
  • 8. Experimental Design and Analysis
  • 9. Multiple Variables and Multiple Hypotheses
  • 10. Classification and Discrimination
  • 11. Survival Analysis and Reliability
  • 12. Which Statistic Should I Use?
  • Appendix 1. Program Your Own Resampling Methods
  • Appendix 2. C++, SC and Stata Code for Permutation Test
  • Appendix 3. SAS and Stata Code for the Bootstrap
  • Appendix 4. Software Sources.