This is a reprint of Peter John classic book on experimental designs originally published by MacMillan but now reprinted by the Society for Industrial and Applied Mathematics in their Classics in Applied Mathematics series. The book was written in 1971 and there have been many changes in philosophy
Statistical Design and Analysis of Experiments (Classics in Applied Mathematics No 22. )
โ Scribed by Peter W. M. John
- Publisher
- Society for Industrial Mathematics
- Year
- 1999
- Tongue
- English
- Leaves
- 381
- Series
- Classics in Applied Mathematics No 22.
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of opt
A indispensable guide to understanding and designing modern experiments <p> The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a moder
This is a reprint of Peter John classic book on experimental designs originally published by MacMillan but now reprinted by the Society for Industrial and Applied Mathematics in their Classics in Applied Mathematics series. The book was written in 1971 and there have been many changes in philosophy
Readers will find this book an invaluable reference on the design of experiments. It contains hard-to-find information on topics such as change-over designs with residual effects and early treatment of analysis of covariance. Other topics include linear models and quadratic forms, experiments with o