The mean absolute percentage error (MAPE) is probably the most widely used goodness-of-fit measure. However, it does not meet the validity criterion due to the fact that the distribution of the absolute percentage errors is usually skewed to the right, with the presence of outlier values. In these cases, MAPE overstates the corresponding population parameter. In this study, we propose an alternative index, called Resistant MAPE or R-MAPE based on the calculation of the Huber M-estimator, which allows overcoming the aforementioned limitation. The results derived from the application of Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models are used to forecast a time series. The arithmetic mean, MAPE, overstates the corresponding population parameter, unlike R-MAPE, on a set of error distributions with a statistically significant right skew, as well as outlier values. Our results suggest that R-MAPE represents a suitable alternative measure of forecast accuracy, due to the fact that it provides a valid assessment of forecast accuracy compared to MAPE.

The aim of this study was to investigate the relationships between math background, trait anxiety, test anxiety, statistics anxiety, attitudes toward statistics and statistics performance in a sample of 472 university students enrolled in statistics courses of Health Sciences majors. A Structural Equation Modeling (SEM) approach showed the attitudes as the stronger direct predictor of performance, and played a full mediating role on the relationship between statistics anxiety and performance. Contrary to hypothesized, the direct contribution of math background, trait anxiety, and test anxiety to performance was non-significant. A final model posited that performance was positively and directly affected by attitudes, and in turn attitudes were positively influenced by math background and negatively affected by anxiety. Math background also appeared as negative predictor of anxiety. Finally, test anxiety was a positively direct predictor of statistics anxiety.