Open AccessON THE SAMPLING THEORY OF RELIABILITY ESTIMATION 1
Author(s) -
Kristof Walter
Publication year - 1969
Publication title -
ets research bulletin series
Language(s) - English
Resource type - Journals
eISSN - 2333-8504
pISSN - 0424-6144
DOI - 10.1002/j.2333-8504.1969.tb00577.x
Subject(s) - normality , reliability (semiconductor) , sampling (signal processing) , point estimation , test (biology) , statistics , computer science , point (geometry) , confidence interval , sampling theory , sample (material) , mathematics , sample size determination , reliability engineering , engineering , power (physics) , paleontology , physics , geometry , chemistry , filter (signal processing) , chromatography , quantum mechanics , computer vision , biology
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 α parameter is derived. The test is then converted to yield confidence intervals for α. 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.