Exploratory model selection was used to find a response model that accounted for the spatial variability present in the experimental results from four examples of spatially designed field experiments. It was found that the class of differential gradients within incomplete blocks was useful for finding a response model that accounted for the spatial variability present in the first example. The class of orthogonal polynomial regressions of response on row and column position and interactions of the regressions was useful for discovering an appropriate response model for the data of examples two, three, and four. The results obtained from the selected response model were compared with standard textbook analyses. Considerable differences in residual mean squares, coefficients of variation, and F-values for treatment to residual mean squares were found. The increase in replication for the selected response model over the textbook response model is demonstrated. The increase can be many fold.