資料來源: Google Book

Introductory statistics with R

  • 作者: Dalgaard, Peter.
  • 出版: New York : Springer ©2002.
  • 稽核項: 1 online resource (xv, 267 pages) :illustrations.
  • 叢書名: Statistics and computing
  • 標題: Estatística (processamento de dados) , COMPUTING , Electronic books. , Statistics , Linguagem de programação. , Statistics Data processing. , Probability & StatisticsGeneral. , R (computerprogramma) , R (Computer program language) , Statistiek. , MATHEMATICS Probability & Statistics -- General. , COMPUTER LANGUAGES , Programação matemática. , Data processing. , Data processing , Mathematical Computing. , MATHEMATICS , Leermiddelen (vorm)
  • ISBN: 0387790543 , 9780387790541
  • ISBN: 9780387954752 , 0387954759
  • 試查全文@TNUA:
  • 附註: Includes bibliographical references (pages 259-260) and index. Cover -- Preface -- Contents -- 1. Basics -- 2. Probability and Distributions -- 3. Descriptive Statistics and Graphics -- 4. One- and Two-Sample Tests -- 5. Regression and Correlation -- 6. Analysis of Variance and the Kruskal-Wallis test -- 7. Tubular Data -- 8. Power and the Computaion of Sample Size -- 9. Multiple Regression -- 10. Linear Models -- 11. Logistic Regression -- 12. Survival Analysis -- A-Obtaining and Installing R -- B-Data Sets In The ISWR Package -- C-Compendium -- Bibliography.
  • 摘要: R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets. The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression. In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix. Peter Dalgaard is associate professor at the Department of Biostatistics at the University of Copenhagen and has extensive experience in teaching within the PhD curriculum at the Faculty of Health Sciences. He has been a member of the R Core Team since 1997.
  • 電子資源: https://dbs.tnua.edu.tw/login?url=https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=99644
  • 系統號: 005322396
  • 資料類型: 電子書
  • 讀者標籤: 需登入
  • 引用網址: 複製連結
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
來源: Google Book
評分