Quality Control with R

An ISO Standards Approach

  • Emilio L. Cano
  • Javier Martinez Moguerza
  • Mariano Prieto
Part of the Use R! book series (USE R)

Table of contents

  1. Front Matter
    Pages i-xxviii
  2. Fundamentals

    1. Front Matter
      Pages 1-1
    2. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 3-28
    3. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 29-92
    4. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 93-118
    5. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 119-142
  3. Statistics for Quality Control

    1. Front Matter
      Pages 143-143
    2. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 145-186
    3. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 187-199
  4. Delimiting and Assessing Quality

    1. Front Matter
      Pages 201-201
    2. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 203-220
    3. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 221-236
  5. Control Charts

    1. Front Matter
      Pages 237-237
    2. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 239-270
    3. Emilio L. Cano, Javier M. Moguerza, Mariano Prieto Corcoba
      Pages 271-284
  6. Back Matter
    Pages 285-349

About this book

Introduction

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.
                                                                                     












Keywords

ISO standards R software quality control quality control with R statistical data modeling

Authors and affiliations

  • Emilio L. Cano
    • 1
  • Javier Martinez Moguerza
    • 2
  • Mariano Prieto
    • 3
  1. 1.Department of Statistics and Operations Campus de FuenlabradaRey Juan Carlos UniversityMadridSpain
  2. 2.Department of Statistics and Operations Campus de FuenlabradaRey Juan Carlos UniversityMadridSpain
  3. 3.ENUSA Industrias AvanzadasMadridSpain

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-24046-6
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-24044-2
  • Online ISBN 978-3-319-24046-6
  • Series Print ISSN 2197-5736
  • Series Online ISSN 2197-5744
  • About this book