presented, for statements with index . scores enable simple interpretation schemes, understandable also in multi-disciplinary project teams. The result of the survey is a single scalar value, in the range of zero to $100$ as a composite measure of the overall usability. The score is computed according to , given $S$ participants, where is the response to $i$ by subject $s$. $$\operatorname{sus}(\mathbf{x}) = \frac{2.5}{S} \sum_{s}\left[\, \sum_{\text{odd } i} \mathbf{x}^\text{SUS}_{s,i} + \sum_{\text{even } i} (4 - \mathbf{x}^\text{SUS}_{s,i})\, \right]
    \label{eq:sus_score}$$ Although the score allows for straightforward comparison of the usability throughout different systems, there is no simple intuition associated with the resulting scalar value. In practice, a of less than $80$ is often interpreted as an indicator of a substantial usability problem with the system. Bangor et al. [@bangor2008empirical; @bangor2009determining] proposed an interpretation of the score in a seven-point scale. : *worst imaginable*, *awful*, *poor*, *OK*, *good*, *excellent*, and *best imaginable*. This mapping also enables an absolute interpretation of a single score.

![Mapping from a score to an adjective rating scheme proposed by Bangor et al. [@bangor2009determining][. Given a rating, the relative height of the Gaussian distributions approximate the probabilities for each adjective. Distributions’ $\mu$ and $\sigma$ were extracted evaluating]{} $959$ surveys 