Abstract
The aim of this paper is to introduce an invariant by translation coefficient different from the variation one (widely used in literature but not fulfilling that property) that allows us to study whether the mean is a good representation of the distribution or not. The value of this new coefficient for a normally distributed random variable is obtained in order to establish a criterion, similar to the one used in the symmetry or kurtosis coefficients, to decide the grade of representation of the mean.
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References
Jobson JD (1991) Applied multivariate data analysis, vol 1. Regression and experimental design. Springer, New York
McPherson G (1990) Statistics in scientific investigation. Its basis, application and interpretation. Springer, New York
Peña D (2002) Análisis de datos multivariantes. McGrawHill/Interamericana de España, Madrid
Rodríguez Muñiz LJ, Tomeo-Perucha V (2011) Métodos Estadísticos para Ingeniería. Garceta Grupo Editorial, Madrid
Acknowledgements
The research in this paper has been partially supported by the Spanish Ministry of Economía and Competitividad Grant MTM2015-63971-P and the Principality of Asturias/FEDER Grant GRUPIN14-101. Their financial support is gratefully acknowledged.
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Bertoluzza, C., Casals, R., Naval, G., Salas, A. (2018). An Alternative to the Variation Coefficient. In: Gil, E., Gil, E., Gil, J., Gil, M. (eds) The Mathematics of the Uncertain. Studies in Systems, Decision and Control, vol 142. Springer, Cham. https://doi.org/10.1007/978-3-319-73848-2_4
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DOI: https://doi.org/10.1007/978-3-319-73848-2_4
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