In many conditions, such as the log-normal model with σ2 = 1.5, 2, the Gamma model with shape equal to 0.5 (monotonically declining pdf) and the Weibull model with shape equal to 0.5 (linearly increasing hazard), as higher skewness data-generating mechanisms, the MAPE from Weibull regression model was always lower than Gamma regression model.
Because of positively skewed data for Anger, EHRV, and alpha-amylase, square root transformed data were analysed, resulting in approximately normal distributions of the data, and skewness and kurtosis were <|2|, except for the kurtosis of Anger which was <3.
In this experiment, the Zipf parameter representing the skewness of data access frequencies varied from 0.5 to 1.5.
It should be noted that the skewness of data from the log-normal and Gamma models increased monotonically as the sample size increased.
For skewness >1, data are log transformed and summarized by group as the geometric mean (and 95% confidence interval).
CRP was transformed into natural logarithm to reduce positive skewness, but data were reported untransformed for clarity.
A test of multivariate normality was used to determine the skewness of data to be used during CFA (41).
Comparing mean and median for each subscale of the SDQ for boys and girls at different ages indicates a slight skewness in data.
To minimize skewness, A/D data of children and adults were normalized in the total samples with the option 'NS' in LISREL 7 (Jöreskog & Sörbom 1989).
In the case of the indicator "Number of kilometres driven per year", the extremely positive skewness of the data led us to use a data transformation.
Skewness from INPS data on the population of workers belonging to firms in the INVIND sample.
