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?...
Regression analysis is vital for understanding relationships between variables, especially when assessing joint significance among multiple predictors. Using the joint F-statistic to compare restricted and unrestricted models in regression analysis, the null hypothesis assumes that excluded variables in the restricted model collectively have no significant effect on the dependent variable.