SELECTION PROCEDURES FOR THE t BEST POPULATIONS

SUMMARY Suppose one has k populations and wishes eventually to choose the "best" one. It is often desirable to use a multi-stage experiment, where at each stage, at least t (~l) populations are selected for further study. This paper is concerned with selecting at least t(~2) populations, presenting generalizations of two methods in existence for t = 1. One method has as its goal the selection of good popUlations, while the other eliminates bad populations. Two special cases considered are the problems of selecting large normal means or small normal variances, and tables are constructed for implementing the procedures. In the case of normal variances, the tables are useful in the classical indifference zone problem. Applications are presented in a variety of fields.