Statistical Analysis: an Introduction using R

This book aims to introduce the principles of statistics and modern statistical analysis for a non-mathematical audience, using the free statistical package R.

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Contents


  • Chapter 1: Assumptions and models 50% developed  as of 10:57, 7 March 2009 (UTC) (10:57, 7 March 2009 (UTC))
  • Chapter 2: Datasets and types of data 50% developed  as of 10:57, 7 March 2009 (UTC) (10:57, 7 March 2009 (UTC))
  • Chapter 3: Statistical models 0% developed  as of 10:57, 7 March 2009 (UTC) (10:57, 7 March 2009 (UTC))
  • Chapter 4: Model formulation and EDA 0% developed  as of 10:57, 7 March 2009 (UTC) (10:57, 7 March 2009 (UTC))
  • Chapter 5: Probability and likelihood 0% developed  as of 10:57, 7 March 2009 (UTC) (10:57, 7 March 2009 (UTC))
  • Chapter 6: The error process 0% developed  as of 09:05, 16 May 2007 (UTC) (09:05, 16 May 2007 (UTC))
Including hypothesis testing
  • Chapter 7: Models for discrete data 0% developed  as of 09:36, 16 May 2007 (UTC) (09:36, 16 May 2007 (UTC))
  • Chapter 8: Models for continuous data 0% developed  as of 09:36, 16 May 2007 (UTC) (09:36, 16 May 2007 (UTC))
  • Chapter 9: Univariate models 0% developed  as of 09:36, 16 May 2007 (UTC) (09:36, 16 May 2007 (UTC))
  •  : to be continued

  • Appendix A: R topics in text 25% developed  as of 10:58, 7 March 2009 (UTC) (10:58, 7 March 2009 (UTC))
These can be used on their own as a basic introduction to R
  • Appendix B: Further references 0% developed  as of 09:36, 16 May 2007 (UTC) (09:36, 16 May 2007 (UTC))
  • Appendix C: Resources for contributors 0% developed  as of 10:08, 29 January 2009 (UTC) (10:08, 29 January 2009 (UTC))
  • Appendix D: Freely available datasets used in the book 0% developed  as of 10:08, 29 January 2009 (UTC) (10:08, 29 January 2009 (UTC))

Authors

Yan

Last modified on 4 February 2013, at 09:18