Design of Comparative Experiments [Hardcover]

The coherent framework behind good practice; for working statisticians, advanced undergraduates, beginning graduate students.For every practising statistician who designs experiments, a coherent framework for the thinking behind good design. Also ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.For every practising statistician who designs experiments, a coherent framework for the thinking behind good design. Also ideal for advanced undergraduate and beginning graduate courses. Examples, exercises and discussion questions are drawn from a wide range of real applications: from drug development, to agriculture, to manufacturing.Design of Comparative Experiments develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. These diagrams are used to elucidate structure, calculate degrees of freedom and allocate treatment sub-spaces to appropriate strata. Good design considers units and treatments first, and then allocates treatments to units. Based on a one-term course the author has taught since 1989, the book is ideal for advanced undergraduate and beginning graduate courses. This book should be on the shelf of every practicing statistician who designs experiments.Preface; 1. Forward look; 2. Unstructured experiments; 3. Simple treatment structure; 4. Blocking; 5. Factorial treatment structure; 6. Row-column designs; 7. Experiments on people and animals; 8. Small units inside large units; 9. More about Latin squares; 10. The calculus of factors; 11. Incomplete-block designs; 12. Factorial designs in incomplete blocks; 13. Fractional factorial designs; 14. Backward look; Exercises; Sources of examples, Questions and exercises; Further reading; Bibliography; Index. ... a carefully planned, well-organized [manner]. Using very lÃ^