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In Support of Null Hypothesis Significance Testing
Proceedings: Biological Sciences
Vol. 271, No. Supplement 3 (Feb. 7, 2004), pp. S82-S84
Published by: Royal Society
Stable URL: http://www.jstor.org/stable/4142564
Page Count: 3
You can always find the topics here!Topics: P values, Statistics, Null hypothesis, Confidence interval, Mathematical dependent variables, Data analysis, Inference, Statistical inferences, Statistical significance, Insect morphology
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Many criticisms have been levelled at null hypothesis significance testing (NHST). It is argued here that although there is reason to doubt that data subjected only to NHST have been subjected to sufficient analysis, the search for clear answers to well-formulated questions derived from substantive hypotheses is well served by NHST. To reliably draw inferences from data, however, NHST may need to be complemented by additional methods of analysis, such as the use of confidence intervals and of estimates of the degree of association between independent and dependent variables. It is argued that these should be seen as complements of, rather than as substitutes for, NHST since they do not directly test the strength of evidence against a null hypothesis.
Proceedings: Biological Sciences © 2004 Royal Society