ABSTRACT
Placing data in the context of the scientific discovery of knowledge through experimentation, Practical Data Analysis for Designed Experiments examines issues of comparing groups and sorting out factor effects and the consequences of imbalance and nesting, then works through more practical applications of the theory. Written in a modern and accessible manner, this book is a useful blend of theory and methods. Exercises included in the text are based on real experiments and real data.
TABLE OF CONTENTS
part A|46 pages
Placing Data in Context
part B|58 pages
Working with Groups of Data
part C|54 pages
Sorting out Effects with Data
part D|48 pages
Dealing with Imbalance
part E|32 pages
Questioning Assumptions
part F|56 pages
Regressing with Factors
part G|40 pages
Deciding on Fixed or Random Effects
part H|46 pages
Nesting Experimental Units
part I|42 pages
Repeating Measures on Subjects