Your Reliability Engineering Professional Development Site
A basic statistical technique for determining the proportion of influence a factor or set of factors has on total variation. It subdivides the total variation of a data set into meaningful component parts associated with specific sources of variation to test a hypothesis on the parameters of the model or to estimate variance components. There are three models: fixed, random, and mixed. ANOVA provides a means to statistically analyze two or more factors at a time.
Our white paper regarding t-test calculations has been very popular. Those that use the t-test tool regularly have commented “I finally understand what it is all about.”
The natural question they ask me next is “have you done anything with the F-test?” It is another common tool and one that is equally misunderstood.
Due to popular request, here is our attempt at explaining the F-test tool, in the two possible methods of use. [Read more…]
Design of Experiments (DoE) and the Analysis of Variance (ANOVA) techniques are economical and powerful methods for determining the statistically significant effects and interactions in multivariable situations. DoE may be utilized for optimizing product designs, as well as for addressing quality and reliability deficiencies. Within the DoE framework, the practitioner may explore the effects of a single variable or analyze multiple variables. [Read more…]