Abstract
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.
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