Modern applied statistics with S. 4th ed.

*(English)*Zbl 1006.62003
Statistics and Computing (Cham). New York, NY: Springer. xi, 495 p. (2002).

From the preface: This is the fourth edition of a book which first appeared in 1994, see the review Zbl 0806.62002, and the \(S\) environment has grown rapidly since. This book concentrates on using the current systems to do statistics; there is a companion volume by the authors, “\(S\)-programming.” (2000; Zbl 0999.62502), which discusses programming in the \(S\) language in much greater depth. Some of the more specialized functionality of the \(S\) environment is covered in on-line complements, additional sections and chapters which are available on the World Wide Web. The datasets and \(S\) functions that we use are supplied with most \(S\) environments and are also available on-line.

This is is not a text in statistical theory, but does cover modern statistical methodology. Each chapter summarizes the methods discussed, in order to set out the notation and the precise method implemented in \(S\). (It will help if the reader has a basic knowledge of the topic of the chapter, but several chapters have been sucessfully used for specialized courses in statistical methods.) Our aim is rather to show how we analyse datasets using \(S\). In doing so we aim to show both how \(S\) can be used and how the availability of a powerful and graphical system has altered the way we approach data analysis and allows penetrating analyses to be performed routinely. Once calculation became easy, the statistician’s energies could be devoted to understanding his or her dataset.

This is is not a text in statistical theory, but does cover modern statistical methodology. Each chapter summarizes the methods discussed, in order to set out the notation and the precise method implemented in \(S\). (It will help if the reader has a basic knowledge of the topic of the chapter, but several chapters have been sucessfully used for specialized courses in statistical methods.) Our aim is rather to show how we analyse datasets using \(S\). In doing so we aim to show both how \(S\) can be used and how the availability of a powerful and graphical system has altered the way we approach data analysis and allows penetrating analyses to be performed routinely. Once calculation became easy, the statistician’s energies could be devoted to understanding his or her dataset.

##### MSC:

62-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics |

62-04 | Software, source code, etc. for problems pertaining to statistics |

65C60 | Computational problems in statistics (MSC2010) |

62-00 | General reference works (handbooks, dictionaries, bibliographies, etc.) pertaining to statistics |

62-07 | Data analysis (statistics) (MSC2010) |

68U99 | Computing methodologies and applications |