For some time it has been well known among specialists in mathematical programming that the statistical problem of fitting a linear multiple regression with the criterion of minimizing the sum of absolute deviations from the regression function (rather than squared deviations) may be reduced to a linear programming problem. But this knowledge seems not widespread among general statisticians.1This note briefly reviews the formulation of this application of linear programming, and its history.