Monte Carlo Simulation of a Modified Chi Distribution Considering Asymmetry in the Generating Functions: Application to the Study of Health-Related Variables

[EN] Random variables in biology, social and health sciences commonly follow skewed distributions. Many of these variables can be represented by exGaussian functions; however, in practice, they are sometimes considered as Gaussian functions when statistical analysis is carried out. The asymmetry can play a fundamental role which can not be captured by central tendency estimators such as the mean. By means of Monte Carlo simulations, the effect of a small asymmetry in the generating functions of the chi distribution is studied. To this end, the k generating functions are taken as exGaussian functions. The limits of this approximation are tested numerically for the practical case of three health-related variables: one physical (body mass index) and two cognitive (verbal fluency and short-term memory). This work is in line with our previous works on a physics-inspired mathematical model to represent the reaction times of a group of individuals. This researchwas partially funded by grant number RTI2018-102256-B-I00 of MINECO/FEDER (Spain). N. Ortigosa acknowledges the support from Generalitat Valenciana under grant Prometeo/2017/102, and from Spanish MINECO under grant MTM2016-76647-P. Ortigosa, N.; Orellana-Panchame, M.; Castro-Palacio, JC.; Fernández De Córdoba, P.; Isidro, J. (2021). Monte Carlo Simulation of a Modified Chi Distribution Considering Asymmetry in the Generating Functions: Application to the Study of Health-Related Variables. Symmetry (Basel). 13(6):1-12. https://doi.org/10.3390/sym13060924