000 02529nam a2200373 i 4500
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003 UkCbUP
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020 _a9781108528825 (ebook)
020 _z9781108423564 (hardback)
020 _z9781108437677 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQA277
_b.P43 2022
082 0 0 _a519.5/6
_223/eng/20211117
100 1 _aP. Fay, Michael,
_eauthor.
245 1 0 _aStatistical hypothesis testing in context :
_breproducibility, inference, and science /
_cMichael P. Fay, Erica H. Brittain.
264 1 _aCambridge :
_bCambridge University Press,
_c2022.
300 _a1 online resource (xiv, 433 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aCambridge series in statistical and probabilistic mathematics ;
_v52
500 _aTitle from publisher's bibliographic system (viewed on 07 Apr 2022).
520 _aFay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation. The emphasis is on equipping applied statisticians with enough tools - and advice on choosing among them - to find reasonable methods for almost any problem and enough theory to tackle new problems by modifying existing methods. After covering the basic mathematical theory and scientific principles, tests and confidence intervals are developed for specific types of data. Essential methods for applications are covered, such as general procedures for creating tests (e.g., likelihood ratio, bootstrap, permutation, testing from models), adjustments for multiple testing, clustering, stratification, causality, censoring, missing data, group sequential tests, and non-inferiority tests. New methods developed by the authors are included throughout, such as melded confidence intervals for comparing two samples and confidence intervals associated with Wilcoxon-Mann-Whitney tests and Kaplan-Meier estimates. Examples, exercises, and the R package asht support practical use.
650 0 _aStatistical hypothesis testing.
700 1 _aBrittain, Erica H.,
_eauthor.
776 0 8 _iPrint version:
_z9781108423564
830 0 _aCambridge series in statistical and probabilistic mathematics ;
_v52.
856 4 0 _uhttps://doi.org/10.1017/9781108528825
942 _2ddc
_cEB
999 _c9776
_d9776