Confidence intervals: nonparametric

Garthwaite, Paul (2005). Confidence intervals: nonparametric. In: Everitt, B.S. and Howell, D.C. eds. Encyclopedia of Statistics in Behavioral Science, Volume 1. Chichester: Wiley, pp. 3475–381.

DOI: https://doi.org/10.1002/0470013192.bsa128

URL: http://eu.wiley.com/WileyCDA/WileyTitle/productCd-...

Abstract

These procedures for forming confidence intervals are attractive because they require weaker assumptions than parametric methods. Several of the procedures exploit the relationship between hypothesis tests and confidence intervals and these require hypotheses to be found that give specified P values. Finding the appropriate hypotheses can be computationally demanding, but for some problems there are efficient search techniques.

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