Publication Type : Journal Article
Publisher : Statistical Papers
Source : Statistical Papers, Volume 53, Number 3, p.531-547 (2012)
Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84864338711&partnerID=40&md5=11d62bdaf4ce5bfa2518790965c9c12c
Campus : Coimbatore
School : School of Engineering
Department : Mathematics
Year : 2012
Abstract : Ever since Professor Bancroft developed inference procedures using preliminary tests there has been a lot of research in this area by various authors across the world. This could be evidenced from two papers that widely reviewed the publications on preliminary test-based statistical methods. The use of preliminary tests in solving doubts arising over the model parameters has gained momentum as it has proven to be effective and powerful over to that of classical methods. Unfortunately, there has been a downward trend in research related to preliminary tests as it could be seen from only few recent publications. Obviously, the benefits of preliminary test-based statistical methods did not reach Six Sigma practitioners as the concept of Six Sigma just took off and it was in a premature state. In this paper, efforts have been made to present a review of the publications on the preliminary test-based statistical methods. Though studies on preliminary test-based methods have been done in various areas of statistics such as theory of estimation, hypothesis testing, analysis of variance, regression analysis, reliability, to mention a few, only few important methods are presented here for the benefit of readers, particularly Six Sigma quality practitioners, to understand the concept. In this regard, the define, measure, analyze, improve and control methodology of six sigma is presented with a link of analyze phase to preliminary test-based statistical methods. Examples are also given to illustrate the procedures. © 2010 Springer-Verlag.
Cite this Research Publication : Dr. Ravichandran J., “A review of preliminary test-based statistical methods for the benefit of Six Sigma quality practitioners”, Statistical Papers, vol. 53, pp. 531-547, 2012.