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## Details

Genre/Form: | Electronic books |
---|---|

Additional Physical Format: | Print version: Braun, John, 1963- First course in statistical programming with R. New York, NY : Cambridge University Press, 2016 (DLC) 2016285382 (OCoLC)944156501 |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
W John Braun; Dundan J Murdoch |

ISBN: | 9781316451090 1316451097 |

OCLC Number: | 953552826 |

Notes: | Includes index. |

Description: | 1 online resource (xiv, 215 pages) : illustrations |

Contents: | Getting Started -- Introduction to the R language -- Programming statistical graphics -- Programming with R -- Simulation -- Computational linear algebra -- Numerical optimization |

Responsibility: | W. John Braun and Duncan J. Murdoch. |

### Abstract:

## Reviews

*Editorial reviews*

Publisher Synopsis

'For what has come to be called data analytics, R is a remarkable tour de force. Strong skills with R programming are needed to allow really effective use. Mastering the content of this carefully staged text is an excellent starting point for gaining those skills.' John Maindonald, Australian National University, Canberra 'This book should be especially useful for those without any prior programming background. The core programming material, such as loops and functions, is postponed to Chapter 4, allowing the student to first become comfortable with R in a broader manner. The placement of Chapter 3, on graphical methods, is particularly helpful in this regard, and is very motivating. The book is written by two recognized experts in the R language, so the reader attains the benefit of being taught by the 'insiders'.' Norm Matloff, University of California, Davis 'This book is an excellent introduction to programming in R. It gently takes the reader from first principles in programming through to more advanced topics such as simulation and plotting. We recommend this book to our graduate students in computational biology as a concise guide to learning R.' Stephen Eglen, University of Cambridge "For what has come to be called data analytics, R is a remarkable tour de force. Strong skills with R programming are needed to allow really effective use. Mastering the content of this carefully staged text is an excellent starting point for gaining those skills." John Maindonald, Australian National University "This book should be especially useful for those without any prior programming background. The core programming material, such as loops and functions, is postponed to Chapter 4, allowing the student to first become comfortable with R in a broader manner. The placement of Chapter 3, on graphical methods, is particularly helpful in this regard, and is very motivating. The book is written by two recognized experts in the R language, so the reader attains the benefit of being taught by the 'insiders'." Norm Matloff, University of California, Davis "This book is an excellent introduction to programming in R. It gently takes the reader from first principles in programming through to more advanced topics such as simulation and plotting. We recommend this book to our graduate students in computational biology as a concise guide to learning R." Stephen Eglen, University of Cambridge Read more...

*User-contributed reviews*