This paper does not present new statistical methods. Rather, it shows that a well known nonparametric procedure which is valid under extremely general conditions also has high efficiency and other favorable properties for certain types of life testing situations. This nonparametric method is the sign test and its confidence interval and point estimate analogs. Sign test procedures and methods of applying them have already received extensive coverage in the literature (e.g., [2]). Consequently, in this paper emphasis is placed on fields of application instead of on methods of application. However, the basic methods for obtaining tests, confidence intervals, and point estimates of the sign test type are restated for convenience. The properties investigated are concerned with the estimation and testing of smaller population percentage points for the case of a sample from a gamma probability distribution. The investigations show that appropriate use of the sign test type of nonparametric tests and estimates sometimes can yield a saving in cost or time without loss of statistical efficiency, since the experiment can be stopped when only a fraction of the items being life tested have failed. The nonparametric results are found to be highly efficient compared to the “best” parametric results based on the same fraction of items failed for the case of small population percentage points; this conclusion appears to be valid for any sample size and for any reasonable type of statistical population.