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

被引:0
作者
Estay, Sergio A. [1 ]
Naulin, Paulette I. [2 ,3 ]
机构
[1] Pontificia Univ Catolica Chile, Ctr Adv Studies Ecol & Biodivers, Santiago 6513677, Chile
[2] Univ Chile, Dept Ciencias Ecol, Santiago, Chile
[3] Univ Chile, Dept Silvicultura & Conservac Nat, Santiago, Chile
来源
BOSQUE | 2011年 / 32卷 / 01期
关键词
NHST; p-values; statistical significance; information criteria; ANOVA; CONFIDENCE-INTERVALS; P-VALUES; STATISTICAL-INFERENCE; TEST CRITERIA; EYE; INSIGNIFICANCE; CRITICISM; EDUCATION; PURPOSES; PICTURES;
D O I
10.4067/S0717-92002011000100001
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Statistical 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.
引用
收藏
页码:3 / 9
页数:7
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