An Intuitive Graphical Approach to Understanding the Split-Plot Experiment


Authors: 
Timothy J. Robinson, William A. Brenneman and William R. Myers
Volume: 
17(1)
Pages: 
online
Year: 
2009
Publisher: 
Journal of Statistics Education
URL: 
http://www.amstat.org/publications/jse/v17n1/robinson.html
Abstract: 

While split-plot designs have received considerable attention in the literature over the past decade, there seems to be a general lack of intuitive understanding of the error structure of these designs and the resulting statistical analysis. Typically, students learn the proper error terms for testing factors of a split-plot design via expected mean squares. This does not provide any true insight as far as why a particular error term is appropriate for a given factor effect. We provide a way to intuitively understand the error structure and resulting statistical analysis in split-plot designs through building on concepts found in simple designs, such as completely randomized and randomized complete block designs, and then provide a way for students to "see" the error structure graphically. The discussion is couched around an example from paper manufacturing.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education