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On Some Principles of Statistical Inference

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  • Nancy Reid
  • David R. Cox

Abstract

type="main" xml:id="insr12067-abs-0001"> Statistical theory aims to provide a foundation for studying the collection and interpretation of data, a foundation that does not depend on the particular details of the substantive field in which the data are being considered. This gives a systematic way to approach new problems, and a common language for summarising results; ideally, the foundations and common language ensure that statistical aspects of one study, or of several studies on closely related phenomena, can be broadly accessible. We discuss some principles of statistical inference, to outline how these are, or could be, used to inform the interpretation of results, and to provide a greater degree of coherence for the foundations of statistics.

Suggested Citation

  • Nancy Reid & David R. Cox, 2015. "On Some Principles of Statistical Inference," International Statistical Review, International Statistical Institute, vol. 83(2), pages 293-308, August.
    • Handle: RePEc:bla:istatr:v:83:y:2015:i:2:p:293-308
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    File URL: http://hdl.handle.net/10.1111/insr.12067
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    1. repec:dau:papers:123456789/555 is not listed on IDEAS
    2. D. R. Cox & Man Yu Wong, 2004. "A simple procedure for the selection of significant effects," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(2), pages 395-400, May.
    3. Min-ge Xie & Kesar Singh, 2013. "Confidence Distribution, the Frequentist Distribution Estimator of a Parameter: A Review," International Statistical Review, International Statistical Institute, vol. 81(1), pages 3-39, April.
    4. John D. Storey, 2002. "A direct approach to false discovery rates," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(3), pages 479-498, August.
    5. Tore Schweder & Nils Lid Hjort, 2002. "Confidence and Likelihood," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 29(2), pages 309-332, June.
    6. Jan Hannig & Thomas C. M. Lee, 2009. "Generalized fiducial inference for wavelet regression," Biometrika, Biometrika Trust, vol. 96(4), pages 847-860.
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    Cited by:

    1. Rubin, Mark, 2020. "Does preregistration improve the credibility of research findings?," MetaArXiv vgr89, Center for Open Science.
    2. David J. Hand, 2022. "Trustworthiness of statistical inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 329-347, January.

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