Suitable for upper level advanced management or cost accounting courses at the undergraduate or MBA/graduate level. Assumes knowledge of management and/or cost accounting. This text provides leading-edge treatment of innovative management accounting issues used by major companies throughout the world. Takes a systematic management- oriented approach to advanced management topics. Each chapter is accompanied by cases to illustrate the concepts discussed.

Graphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.

Graphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.

The chapters in this volume present the state of optimum experimental design at the beginning of the new millennium, with an emphasis on developing areas. The contributions range from theory to applications, starting with a glimpse back to the beginnings of optimum experimental design. Theoretical chapters cover the properties and methods of construction of designs. Applications include chapters on sequential design problems in the pharmaceutical industry and on the designs with discrete factors in agriculture. There are chapters on training neural networks, on the efficient selection of sampling methods, and on problems arising in glass making and in herbicide resistance of Brazilian weeds. The contributors, from a variety of countries, include many acknowledged experts whose work reflects the international spread of activity in the subject. Audience: Experimentalists as well as research workers and students in statistics will find much to interest them in these papers.

I truly believe in miracles. I am a true testament of a collection of miracles. For those of you who are not a believer of God, I hope my story will bring you closer to believing the possibility of a divine creator. The belief that I had about God as a child carried me through life in what I would describe as a protective bubble. The negative, the unpleasant, the horrific seem to have no profound affect on me .It would not last long in my present. A goodness will come to my aid. I am forever grateful for this miracle. In my story you will recognize these miracles first hand. These miracles are helping me live a fulfilled life in which I help others along my journey. In the story you will see that I try to be a fair minded person but sometime the negativity of nature overwhelmed me and I had to strike .I try to be as merciful as possible. In the book you will see how the miracles in life shaped and guide me thru out my life today. I am no saint but I will do what is right most of the time. Hope you enjoy the book.

Experiments on patients, processes or plants all have random error, making statistical methods essential for their efficient design and analysis. This book presents the theory and methods of optimum experimental design, making them available through the use of SAS programs. Little previous statistical knowledge is assumed. The first part of the book stresses the importance of models in the analysis of data and introduces least squares fitting and simple optimum experimental designs. The second part presents a more detailed discussion of the general theory and of a wide variety of experiments. The book stresses the use of SAS to provide hands-on solutions for the construction of designs in both standard and non-standard situations. The mathematical theory of the designs is developed in parallel with their construction in SAS, so providing motivation for the development of the subject. Many chapters cover self-contained topics drawn from science, engineering and pharmaceutical investigations, such as response surface designs, blocking of experiments, designs for mixture experiments and for nonlinear and generalized linear models. Understanding is aided by the provision of "SAS tasks" after most chapters as well as by more traditional exercises and a fully supported website. The authors are leading experts in key fields and this book is ideal for statisticians and scientists in academia, research and the process and pharmaceutical industries.