ABSTRACT
logistical regression analysis is applicable for any combination of discrete and continuous variables, and represents an alternative classification when the multivariate normal model is not justified. Models involving qualitative choice are especially applicable for survey data, where individuals are asked opinions or are directed to indicate degrees of agreement or satisfaction. Mills that produce for foreign markets often need to cut and store large volumes of lumber before reprocessing, drying in dry kilns, and concentrate in large enough shipments for export. Statistical methods were selected which might help measure various business factors’ effect on export success and the magnitude of that effect. Logistical regression has been applied in many forest economics and other related disciplines. Stepwise regression has been commonly used to select potential variables for models and has been used to pick from large numbers of variables in other disciplines.
