Skewness and kurtosis are essential measures that help describe the shape of a data distribution. While both are moments * of the distribution, they serve different purposes and utilize different mathematical approaches to capture unique aspects of data behavior. A particularly interesting point of differentiation between these two metrics is the power to which the deviations from the mean are raised: skewness uses the third power, while kurtosis uses the fourth power. But why is this the case?...