Quality Control with R pp 3-28

Part of the Use R! book series (USE R)

| Cite as

An Intuitive Introduction to Quality Control with R

  • Emilio L. Cano
  • Javier M. Moguerza
  • Mariano Prieto Corcoba
Chapter

Abstract

This chapter introduces Quality Control by means of an intuitive example. Furthermore, that example is used to illustrate how to use the R statistical software and programming language for Quality Control. A description of R outlining its advantages is also included in this chapter, all in all paving the way to further investigation throughout the book.

References

  1. 1.
    Cano, E.L., Moguerza, J.M., Redchuk, A.: Six Sigma with R. Statistical Engineering for Process Improvement. Use R!, vol. 36. Springer, New York (2012). http://www.springer.com/statistics/book/978-1-4614-3651-5
  2. 2.
    Chambers, J.M.: Software for Data Analysis. Programming with R. Statistics and Computing. Springer, Berlin (2008)CrossRefMATHGoogle Scholar
  3. 3.
    Free Software Foundation, Inc.: Free Software Foundation website. http://gnu.org (2014). Accessed 10 July 2014
  4. 4.
  5. 5.
    Ihaka, R., Gentleman, R.: R: a language for data analysis and graphics. J. Comput. Graph. Stat. 5, 299–314 (1996)Google Scholar
  6. 6.
    ISO TC69/SC1–Terminology and Symbols: ISO 3534-1:2006 - Statistics – Vocabulary and symbols – Part 1: General statistical terms and terms used in probability. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40145 (2010)
  7. 7.
    ISO TC69/SC1–Terminology and Symbols: ISO 3534-2:2006 - Statistics – Vocabulary and symbols – Part 2: Applied statistics. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40147 (2014)
  8. 8.
    ISO TC69/SC4–Applications of statistical methods in process management: ISO 11462-1:2001 - Guidelines for implementation of statistical process control (SPC) – Part 1: Elements of SPC. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=33381 (2012)
  9. 9.
    ISO TC69/SC4–Applications of statistical methods in process management: ISO 7870-2:2013 - Control charts – Part 2: Shewhart control charts. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=40174 (2013)
  10. 10.
    ISO TC69/SC4–Applications of statistical methods in process management: ISO 22514-1:2014 - Statistical methods in process management – Capability and performance – Part 1: General principles and concepts. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=64135 (2014)
  11. 11.
    ISO TC69/SC4–Applications of statistical methods in process management: ISO 7870-1:2014 - Control charts – Part 1: General guidelines. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=62649 (2014)
  12. 12.
    ISO TC69/SC6–Measurement methods and results: ISO 5725-1:1994 - Accuracy (trueness and precision) of measurement methods and results – Part 1: General principles and definitions. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=11833 (2012)
  13. 13.
    ISO TC69/SC6–Measurement methods and results: ISO 10576-1:2003 - Statistical methods – Guidelines for the evaluation of conformity with specified requirements – Part 1: General principles. Published standard. http://www.iso.org/iso/catalogue_detail.htm?csnumber=32373 (2014)
  14. 14.
    Leisch, F.: Sweave: dynamic generation of statistical reports using literate data analysis. In: Härdle, W., Rönz, B. (eds.) Compstat 2002 — Proceedings in Computational Statistics, pp. 575–580. Physica, Heidelberg (2002). http://www.stat.uni-muenchen.de/~leisch/Sweave
  15. 15.
    R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2015). http://www.R-project.org/
  16. 16.
    Shewhart, W.: Economic Control of Quality in Manufactured Products. Van Nostrom, New York (1931)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Emilio L. Cano
    • 1
    • 2
  • Javier M. Moguerza
    • 1
  • Mariano Prieto Corcoba
    • 3
  1. 1.Department of Computer Science and StatisticsRey Juan Carlos UniversityMadridSpain
  2. 2.Statistics Area, DHEPThe University of Castilla-La ManchaCiudad RealSpain
  3. 3.ENUSA Industrias AvanzadasMadridSpain

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