Statistical significance testing - a panacea for software technology experiments?

被引:24
|
作者
Miller, J [1 ]
机构
[1] Univ Alberta, Dept Elect & Comp Engn, STEAM Res Ctr, Edmonton, AB T6H 5M3, Canada
关键词
empirical; hypothesis; replication;
D O I
10.1016/j.jss.2003.12.019
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Empirical software engineering has a long history of utilizing statistical significance testing, and in many ways, it has become the backbone of the topic. What is less obvious is how much consideration has been given to its adoption. Statistical significance testing was initially designed for testing hypotheses in a very different area, and hence the question must be asked: does it transfer into empirical software engineering research? This paper attempts to address this question. The paper finds that this transference is far from straightforward, resulting in several problems in its deployment within the area. Principally problems exist in: formulating hypotheses, the calculation of the probability values and its associated cut-off value, and the construction of the sample and its distribution. Hence, the paper concludes that the topic should explore other avenues of analysis, in an attempt to establish which analysis approaches are preferable under which conditions, when conducting empirical software engineering studies. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:183 / 192
页数:10
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