Along which paths should experimental statistics develop? By recognizing the selection of an “experimental design” as the selection of a pattern, as only a small part of designing an experiment. By developing further the possibilities of restricted randomization. By learning to consciously balance bias and variability, especially in regression situations. By developing experimental patterns, such as pieces of mixed factorials, which provide desired properties at far lower cost and by using estimates of only 90–95% efficiency. By recognizing the effect of distinct aims in diversifying well-chosen methods. By looking to new sources of stimulation, such as experiments involving very many factors, problems of tolerance design and application, and those statistical techniques really appropriate to research. By looking more and more frequently at broader canvas, considering investigations rather than single experiments.