國立虎尾科技大學 |

Statistical hypothesis testing in context : = reproducibility, inference, and science /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Statistical hypothesis testing in context :/ Michael P. Fay, Erica H. Brittain.
Reminder of title:	reproducibility, inference, and science /
Author:	P. Fay, Michael,
other author:	Brittain, Erica H.,
Description:	1 online resource (xiv, 433 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 07 Apr 2022).
Subject:	Statistical hypothesis testing. -
Online resource:	https://doi.org/10.1017/9781108528825
ISBN:	9781108528825 (ebook)

Statistical hypothesis testing in context : = reproducibility, inference, and science /
P. Fay, Michael,

Statistical hypothesis testing in context :reproducibility, inference, and science /Michael P. Fay, Erica H. Brittain. - 1 online resource (xiv, 433 pages) :digital, PDF file(s). - Cambridge series in statistical and probabilistic mathematics ;52. - Cambridge series in statistical and probabilistic mathematics ;53..

Title from publisher's bibliographic system (viewed on 07 Apr 2022).

Fay 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.

ISBN: 9781108528825 (ebook)Subjects--Topical Terms:

527723
Statistical hypothesis testing.

LC Class. No.: QA277 / .P43 2022

Dewey Class. No.: 519.5/6

Statistical hypothesis testing in context : = reproducibility, inference, and science /
LDR:02262nam a2200301 i 4500 001 1126056
003 UkCbUP
005 20220420193104.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 240926s2022||||enk o ||1 0|eng|d
020 $a 9781108528825 (ebook)
020 $z 9781108423564 (hardback)
020 $z 9781108437677 (paperback)
035 $a CR9781108528825
040 $a UkCbUP $b eng $e rda $c UkCbUP
050 0 0 $a QA277 $b .P43 2022
082 0 0 $a 519.5/6 $2 23/eng/20211117
100 1 $a P. Fay, Michael, $e author. $3 1444651
245 1 0 $a Statistical hypothesis testing in context : $b reproducibility, inference, and science / $c Michael P. Fay, Erica H. Brittain.
264 1 $a Cambridge : $b Cambridge University Press, $c 2022.
300 $a 1 online resource (xiv, 433 pages) : $b digital, PDF file(s).
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
490 1 $a Cambridge series in statistical and probabilistic mathematics ; $v 52
500 $a Title from publisher's bibliographic system (viewed on 07 Apr 2022).
520 $a Fay 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 $a Statistical hypothesis testing. $3 527723
700 1 $a Brittain, Erica H., $e author. $3 1444652
776 0 8 $i Print version: $z 9781108423564
830 0 $a Cambridge series in statistical and probabilistic mathematics ; $v 53. $3 1405725
856 4 0 $u https://doi.org/10.1017/9781108528825