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Transformation of Mean Opinion Scores to Avoid Misleading of Ranked based Statistical Techniques
Citation key naderi2020c
Author Naderi, Babak and Möller, Sebastian
Title of Book 12th International Conference on Quality of Multimedia Experience (QoMEX)
Pages 1–3
Year 2020
ISBN 978-1-7281-5965-2
Month may
Publisher IEEE
Series QoMEX
How Published Poster
Abstract The rank correlation coefficients and the rankedbased statistical tests (as a subset of non-parametric techniques) might be misleading when they are applied to subjectively collected opinion scores. Those techniques assume that the data is measured at least at an ordinal level and define a sequence of scores to represent a tied rank when they have precisely an equal numeric value. In this paper, we show that the definition of tied rank, as mentioned above, is not suitable for Mean Opinion Scores (MOS) and might be misleading conclusions of rank-based statistical techniques. Furthermore, we introduce a method to overcome this issue by transforming the MOS values considering their 95% Confidence Intervals. The rank correlation coefficients and ranked-based statistical tests can then be safely applied to the transformed values. We also provide open-source software packages in different programming languages to utilize the application of our transformation method in the quality of experience domain.
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