Title: Inferences for a Skew-Normal Distribution

Abstract: A three parameter Skew-Normal distribution (SND), which is an interesting generalization of the usual two parameter normal distribution, is getting a lot of attention lately due to its flexibility to accommodate both positively skewed as well as negatively skewed shapes, apart from the symmetric shape, to model various types of datasets. Though a lot of work has been done to characterize SND, and deriving many of its distributional properties, relatively less efforts have been devoted to inferences on the model parameters due to some intrinsic complexities. In this talk we will focus on hypothesis testing on the location parameter of SND with an application of comparing two Gamma distribution means.