Paper suggests a new approach to analysis of field experiment results. The outset point are both the analysis of spatial variation and an assumption that the basis of the analysis is a plot and its position in the field. The occurrence of spatial variation can be a prerequisite to the purposefulness of applying more sophisticated methods to data analysis. If given spatial structure of the variation is confirmed, one can expect the application of alternative methods to data analysis will be more efficient than the classical ones. If spatial variation is random then traditional statistical techniques will be sufficiently effective. Tue Smith 's b index of soil variability and the autocorrelogram and semivariogram analyses were applied to evaluation of the soil variability while the Papadakis 's NNA and kriging were used to remove the spatial effects. It was stated that the magniture of b index, simple to measure in present experiment where the blocks were apphed, can point to purposefulness of detailed analysis of the background variation in the experiment and possible gain in experiment effectiveness.
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