This paper is intended as a contribution to the sampling theory of reliability estimation when a test has been divided into two, not necessarily parallel, parts. Under normality assumptions, a strict t-test of a point hypothesis about the coefficient a parameter is derived. The test is then converted to yield confidence intervals for a. These techniques remain applicable even when the initial distributional assumption is considerably relaxed. The methods developed here are complementary to certain large sample techniques of the same intent. Worked examples are appended by way of illustration.
