ABSTRACT
The role of statistics in experimental design has been to separate the observed differences into those caused by various factors and those due to random fluctuation. The classical method used to separate these differences is analysis of variance, or ANOVA. In general, the method consists of looking at the total variation in the data, breaking it into its various "accountable for" components, and running statistical tests in an attempt to find out which components influence the experiment. The specific ANOVA heavily depends on the design of the experiment. Functional specification analysis is similar to the cause-and-effect diagram but is better suited to design and product engineers. The implementation of the recommendations developed by the team is, of course, a management decision. The purpose of scientific investigation is to develop a realistic type of experiment, assure proper running of the experiment, and find dependable results.
