The selection of the best subset of variables in a linear model is generally produccd by obtaining the regression equation that satisfies an optimality criterion. Unfortunately the statistical properties of the selected regression equations are not described by a general theory and in fact very, little is known of these properties. In this paper the different possible models are compared in ternls of a risk function. The properties of the risk function are used to study the effect of rejecting nonsignificant variables.