Data analysis in forest sciences: why do we continue using null hypothesis significance tests?

dc.creatorEstay,Sergio A
dc.creatorNaulin,Paulette I
dc.date2011-01-01
dc.date.accessioned2017-03-07T16:34:43Z
dc.date.available2017-03-07T16:34:43Z
dc.identifierhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0717-92002011000100001
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/403979
dc.descriptionStatistical methods are indispensable for scientific research. In forest sciences, the use of null hypothesis significance tests (NHSTs) has been the rule of thumb to judge hypotheses or associations among variables, in spite of the multiple problems of these techniques and the several criticisms published for many years in other scientific areas. In this review, the origin of current techniques, their most important problems, and some alternatives that are known to most forest researchers are shown. Persistence in using NHSTs, instead of better statistical methods or without adequate complements, could render our work inefficient and risky. Reasons for the permanence of NHSTs in forest sciences are discussed.
dc.formattext/html
dc.languageen
dc.publisherUniversidad Austral de Chile, Facultad de Ciencias Forestales
dc.sourceBosque (Valdivia) v.32 n.1 2011
dc.subjectNHST
dc.subjectp-values
dc.subjectstatistical significance
dc.subjectinformation criteria
dc.subjectANOVA
dc.titleData analysis in forest sciences: why do we continue using null hypothesis significance tests?
dc.typeArtículos de revistas


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