A new extended mixture normal distribution

Sa？etak The normal distribution is the most important model in statistics for analysis of continuous data. We propose a new distribution, called the extended mixture normal distribution, based on a linear mixture model. We obtain explicit expressions for the ordinary and incomplete moments, generating and quantile functions, mean deviations and two measures of entropy. The maximum likelihood and Bayesian methods are used to estimate the model parameters. We prove empirically that the new distribution can be a better model than the normal and other classical distributions by means of an application to real data