Skip to main content

Introduction

  • Chapter
  • First Online:
Statistical Decision Theory

Part of the book series: SpringerBriefs in Statistics ((BRIEFSSTATIST))

  • 2584 Accesses

Abstract

Most statisticians are accustomed to concluding the formal part of their analysis by one or several estimates.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Berger, J. O. (1985). Statistical decision theory and bayesian analysis (2nd ed.). NewYork: Springer-Verlag.

    Book  MATH  Google Scholar 

  • DeGroot, M. H. (2004). Optimal statistical decisions. New York: McGraw-Hill.

    Book  MATH  Google Scholar 

  • Ferguson, T. S. (1969). Mathematical statistics: A decision theoretical approach. New York: Academic Press.

    Google Scholar 

  • Lindley, D. V. (1985). Making decisions (2nd ed.). Chichester, UK: Wiley.

    Google Scholar 

  • Neyman, J., & Pearson, E. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London Series A, 231, 289–337.

    Article  Google Scholar 

  • Longford, N. (2005). Editorial: Model selection and efficiency. Is ‘Which model..?’ the right question? Journal of the Royal Statistical Society Series A, 168, 469–472.

    Article  MathSciNet  Google Scholar 

  • Longford, N. T. (2007). Playing consequences [Letter to the Editor]. Significance, 4, 46.

    Google Scholar 

  • Longford, N. T. (2008). An alternative analysis of variance. SORT, Journal of the Catalan Institute of Statistics, 32, 77–91.

    Google Scholar 

  • R Development Core Team (2009). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

    Google Scholar 

  • Raiffa, H., & Schlaifer, R. (1961). Applied statistical decision theory. Boston, MA: Harvard Business School.

    Google Scholar 

  • Savage, L. J. (1951). The theory of statistical decision. Journal of the American Statistical Association, 46, 55–67.

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nicholas T. Longford .

Rights and permissions

Reprints and permissions

Copyright information

© 2013 The Author

About this chapter

Cite this chapter

Longford, N.T. (2013). Introduction. In: Statistical Decision Theory. SpringerBriefs in Statistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40433-7_1

Download citation

Publish with us

Policies and ethics