One-Way Classification

Abstract

In this chapter we consider the analysis of variance associated with experiments having only one factor or experimental variable. Such an experimental layout is commonly known as one-way classification in which sample observations are classified (grouped) by only a single criterion. It provides the simplest data structure containing one or more observations at every level of a single factor. One-way classification is a very useful model in statistics. Many complex experimental situations can often be considered as one-way classification. In the succeeding chapters, we discuss situations involving two or more experimental variables.