This book aims to introduce the principles of statistics and modern statistical analysis for a non-mathematical audience, using the free statistical packageR.
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Contents
- Chapter 1: Assumptions and models
(10:57, 7 March 2009 (UTC)) - Chapter 2: Datasets and types of data
(10:57, 7 March 2009 (UTC)) - Chapter 3: Statistical models
(10:57, 7 March 2009 (UTC)) - Chapter 4: Model formulation and EDA
(10:57, 7 March 2009 (UTC)) - Chapter 5: Probability and likelihood
(10:57, 7 March 2009 (UTC)) - Chapter 6: The error process
(09:05, 16 May 2007 (UTC))
- Including hypothesis testing
- Chapter 7: Models for discrete data
(09:36, 16 May 2007 (UTC)) - Chapter 8: Models for continuous data
(09:36, 16 May 2007 (UTC)) - Chapter 9: Univariate models
(09:36, 16 May 2007 (UTC)) - : to be continued
- Appendix A: R topics in text
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- These can be used on their own as a basic introduction to R
- Appendix B: Further references
(09:36, 16 May 2007 (UTC)) - Appendix C: Resources for contributors
(10:08, 29 January 2009 (UTC)) - Appendix D: Freely available datasets used in the book
(10:08, 29 January 2009 (UTC))
Authors
Yan