This paper reports a quantitative assessment of the statistical power of empirical software engineering research based on the 103 papers on controlled ...
The review revealed that software engineering experiments were generally designed with unacceptably low power and that inadequate attention was paid to ...
Feb 20, 2020 · Bibliographic details on A systematic review of statistical power in software engineering experiments.
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Jun 13, 2016 · This paper reports a quantitative assessment of the statistical power of empirical software engineering research based on the 103 papers on ...
Jun 6, 2024 · FOERRT: A systematic review of statistical power in software engineering experiments. This Paper is available in English.
This paper provides preliminary evidence that SE research suffers from the same statistical problems as other experimental disciplines.
The review investigates the practice of effect size reporting, summarizes standardized effect sizes detected in the experiments, discusses the results and gives ...
This document summarizes basics of hypothesis testing and statistic power analysis, and then illustrates how to do using SAS 9, Stata 10, G*Power 3.
Objective: The purpose of this work was to assess the quality of published experiments in software engineering with respect to the validity of inference and ...
Abstract. An effect size quantifies the effects of an experimental treatment. Conclusions drawn from hypothesis testing results might be erroneous if effect ...