Practical Data Analysis for Designed Experiments places data in the context of the scientific discovery of knowledge through experimentation and examines issues of comparing groups and sorting out factor effects. The consequences of imbalance and nesting in design are considered before concluding with more practical applications of the theory.

Throughout the book there are practical guidelines for formal data analysis and graphical representation of results. The book offers numerous examples with SAS and S-Plus instructions which are available on the Internet.

The text is aimed at statisticians and scientists, with enough theory and examples to help the reader understand the analysis of standard and nonstandard experimental designs. Graduate and research level biostatisticians and biologists will find the book of particular interest, and it will also be valued by data analysts and statistical consulting team members.