into plots, assigns plots to a new treatment or a standard control at random, ignores the random assignment Z and applies in all cases the standard fertilizer, insecticide, etc., and ultimately harvests the crops recording yields in each plot. Essentially, the farmer cooperated in setting up an experiment and recording results, but he work the farm in the usual way, harvesting the usual crops for sale. This produced a simulated experiment with real crops in which the null hypothesis of no treatment e⁄ect is known to be true. For instance, by comparing two uniformity trials, perhaps at the same farm, one might discover that the estimated standard error is smaller from a uniformity trial designed as a Latin square than another uniformity trial designed as randomized blocks. In a certain era, statisticians did this, so in our era it is easy to imagine something that was once actually done. We deGLYPH<133>ne the treatment e⁄ect with interference with reference to a uniformity trial. Stated informally, the e⁄ect a treatment with interference is a comparison of what happened in the actual experiment with its active treatment to what would have happened in a uniformity trial with the same treatment assignment Z but no active treatment. As in an era gone by, it is a comparison of two whole experiments, rather than a comparison of a treated and a control group. With interference, both treated and control units are a⁄ected by treatments applied to other units, so a comparison of a treated and a control group is not a comparison of a treated and an untreated situation. A comparison of an experiment with an active treatment and a uniformity trial is a comparison of a treated and an untreated situation. In §1.3, this is a comparison of an experiment with randomized stop and go trials and an experiment of identical structure with only go trials. Conveniently, using a few technical tools in §3.3 that were not available in 1937, we can make inferences about a uniformity trial that was never performed with the aid of a distribution-free pivotal quantity. 14