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Bayesian Data Analysis in Empirical Software Engineering Research
Statistics comes in two main flavors: frequentist and Bayesian. For hist...
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An Overview of Statistical Data Analysis
The use of statistical software in academia and enterprises has been evo...
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Useful Statistical Methods for Human Factors Research in Software Engineering: A Discussion on Validation with Quantitative Data
In this paper we describe the usefulness of statistical validation techn...
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VERIFAS: A Practical Verifier for Artifact Systems
Data-driven workflows, of which IBM's Business Artifacts are a prime exp...
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Exploring the Mysteries of System-Level Test
System-level test, or SLT, is an increasingly important process step in ...
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Data of low quality is better than no data
Missing data is not uncommon in empirical software engineering research ...
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A Variability-Aware Design Approach to the Data Analysis Modeling Process
The massive amount of current data has led to many different forms of da...
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Application of Statistical Methods in Software Engineering: Theory and Practice
The experimental evaluation of the methods and concepts covered in software engineering has been increasingly valued. This value indicates the constant search for new forms of assessment and validation of the results obtained in Software Engineering research. Results are validated in studies through evaluations, which in turn become increasingly stringent. As an alternative to aid in the verification of the results, that is, whether they are positive or negative, we suggest the use of statistical methods. This article presents some of the main statistical techniques available, as well as their use in carrying out the implementation of data analysis in experimental studies in Software Engineering. This paper presents a practical approach proving statistical techniques through a decision tree, which was created in order to facilitate the understanding of the appropriate statistical method for each data analysis situation. Actual data from the software projects were employed to demonstrate the use of these statistical methods. Although it is not the aim of this work, basic experimentation and statistics concepts will be presented, as well as a concrete indication of the applicability of these techniques.
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