‎The classic F-test is usually used for testing the effects of factors in homoscedastic two-way ANOVA models‎. ‎However‎, ‎the assumption of equal cell variances is usually violated in practice‎. ‎In recent years‎, ‎several test procedures have been proposed for testing the effects of factors‎. ‎In this paper‎, ‎the two methods that are approximate degree of freedom (ADF) and parametric bootstrap (PB) approaches are evaluated in terms of type one error and power‎. ‎The simulation results show that these two methods have satisfactory performance in terms of type one error and their power is very close to each other approximately‎. ‎However‎, ‎the ADF method is very easy to implement in comparison with PB appreach which is simulation-based method and consequently time consuming‎.  

‎Normal distribution is widely used in many applications‎. ‎The problem of testing whether observations come from a normal distribution has been studied extensively by many researchers‎. ‎Our main goal in this article is to present a simple test procedure for testing multivariate ‎normality‎‎.