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Lecture Notes in Computer Science
Software Engineering (SE) experiments are traditionally analyzed with statistical tests (e.g., t-tests, ANOVAs, etc.) that assume equally spread data across treatments (i.e., the homogeneity of variances assumption). Differences across treatments' variances in SE are not seen as an opportunity to gain insights on technology performance, but instead, as a hindrance to analyze the data. We have studied the role of variance in mature experimental disciplines such as medicine. We illustrate thedoi:10.1007/978-3-030-03673-7_13 fatcat:3wilrwi6sfhk5ky6kct3rkkd2u