This book continues where DOE Simplified leaves off in Chapter 8 with an introduction to "Response Surface Methods [RSM] for Optimization." It presents this advanced tool for design of experiments (DOE) in a way that anyone with a minimum of technical training can understand and appreciate. Unlike any other book of its kind, RSM Simplified keeps formulas to a minimum-making liberal use of figures, charts, graphs and checklists. It also offers many relevant examples, amusing and fun do-it-yourself exercises.

Many chemists - especially those most brilliant in their field - fail to appreciate the power of planned experimentation. They dislike the mathematical aspects of statistical analysis. In addition, these otherwise very capable chemists also dismissed predictive models based only on empirical data. Ironically, in the hands of subject matter experts like these elite chemists, the statistical methods of mixture design and analysis provide the means for rapidly converging on optimal compositions. What differentiates Formulation Simplified from the standard statistical texts on mixture design is that the authors make the topic relatively easy and fun to read. They provide a whole new collection of insighful original studies that illustrate the essentials of mixture design and analysis. Solid industrial examples are offered as problems at the end of many chapters for those who are serious about trying new tools on their own. Statistical software to do the computations can be freely accessed via a web site developed in support of this book.

Anderson and Whitcomb pick up where they left off in DOE Simplified with RSM Simplified -- a practical tool for design of experiments that anyone with a minimum of technical training can understand and appreciate. Their approach is simple and fun for those who desire knowledge on response surface methods but are put off by the academic nature of other books on the topic. RSM Simplified keeps formulas to a minimum and makes liberal use of figures, charts, graphs, and checklists. It offers many relevant examples with amusing sidebars and do-it-yourself exercises that will lead readers to the peak potential for their product quality and process efficiency.

Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation.Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes.The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration.This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments.Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.

Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors' decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation. Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes. The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration. This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments. Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.

Many chemists - especially those most brilliant in their field - fail to appreciate the power of planned experimentation. They dislike the mathematical aspects of statistical analysis. In addition, these otherwise very capable chemists also dismissed predictive models based only on empirical data. Ironically, in the hands of subject matter experts like these elite chemists, the statistical methods of mixture design and analysis provide the means for rapidly converging on optimal compositions. What differentiates Formulation Simplified from the standard statistical texts on mixture design is that the authors make the topic relatively easy and fun to read. They provide a whole new collection of insighful original studies that illustrate the essentials of mixture design and analysis. Solid industrial examples are offered as problems at the end of many chapters for those who are serious about trying new tools on their own. Statistical software to do the computations can be freely accessed via a web site developed in support of this book.