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Praise for the First Edition : If you ...want an up-to-date, definitive reference written by authors who have contributed much to this field, then this book is an essential addition to your library. - Journal of the American Statistical Association Fully updated to reflect the major progress in the use of statistically designed experiments for product and process improvement, Experiments , Second Edition introduces some of the newest discoveries-and sheds further light on existing ones-on the design and analysis of experiments and their applications in system optimization, robustness, and treatment comparison. Maintaining the same easy-to-follow style as the previous edition while also including modern updates, this book continues to present a new and integrated system of experimental design and analysis that can be applied across various fields of research including engineering, medicine, and the physical sciences. The authors modernize accepted methodologies while refining many cutting-edge topics including robust parameter design, reliability improvement, analysis of non-normal data, analysis of experiments with complex aliasing, multilevel designs, minimum aberration designs, and orthogonal arrays. Along with a new chapter that focuses on regression analysis, the Second Edition features expanded and new coverage of additional topics, including: Expected mean squares and sample size determination One-way and two-way ANOVA with random effects Split-plot designs ANOVA treatment of factorial effects Response surface modeling for related factors Drawing on examples from their combined years of working with industrial clients, the authors present many cutting-edge topics in a single, easily accessible source. Extensive case studies, including goals, data, and experimental designs, are also included, and the book's data sets can be found on a related FTP site, along with additional supplemental material. Chapter summaries provide a succinct outline of discussed methods, and extensive appendices direct readers to resources for further study. Experiments , Second Edition is an excellent book for design of experiments courses at the upper-undergraduate and graduate levels. It is also a valuable resource for practicing engineers and statisticians.
The term scienti?c inquiry as manifest in different educational settings covers a wide range of diverse activities. The differences in types of scienti?c inquiry can be organized along a continuum according to the degree of teacher control and intellectual sophistication involved in each type of inquiry. Types of scienti?c inquiry can also be de?ned according to whether they produce cultural knowledge or personal knowledge. Authentic scienti?c inquiry is de?ned according to ?ve characteristics: devel- ment of personal and cultural knowledge; contextualized scienti?c knowledge; the progression toward high-order problem solving; social interaction for s- enti?c goals; and scienti?c inquiry as a multi-stage and multi-representational process. The de?nition of scienti?c inquiry that forms the basis for the development of an assessment program consists of a two-part analytical frame: the de?nition of knowledge types relevant to scienti?c inquiry and the de?nition of an organi- tional frame for these knowledge types. Four types of knowledge are signi?cant for the de?nition of a speci?c s- enti?c inquiry program: cognitive knowledge, physical knowledge, represen- tional knowledge, and presentational knowledge. All four of these knowledge types are considered signi?cant. These four types of knowledge are organized in a framework that consists of two intersecting axes: the axis of knowledge types and the axis of stages of a s- ci?c scienti?c inquiry. This framework describes scienti?c inquiry as multi-stage process that involves the development of a series of in-lab outcomes (represen- tions) over an extended period of time.
A bestseller for nearly 25 years, Analysis of Messy Data, Volume 1: Designed Experiments helps applied statisticians and researchers analyze the kinds of data sets encountered in the real world. Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since the original publication. New to the Second Edition Several modern suggestions for multiple comparison procedures Additional examples of split-plot designs and repeated measures designs The use of SAS-GLM to analyze an effects model The use of SAS-MIXED to analyze data in random effects experiments, mixed model experiments, and repeated measures experiments The book explores various techniques for multiple comparison procedures, random effects models, mixed models, split-plot experiments, and repeated measures designs. The authors implement the techniques using several statistical software packages and emphasize the distinction between design structure and the structure of treatments. They introduce each topic with examples, follow up with a theoretical discussion, and conclude with a case study. Bringing a classic work up to date, this edition will continue to show readers how to effectively analyze real-world, nonstandard data sets.
The challenges and rewards of scientific collaboration enabled by information and communication technology, from theoretical approaches to in-depth case studies. Modern science is increasingly collaborative, as signaled by rising numbers of coauthored papers, papers with international coauthors, and multi-investigator grants. Historically, scientific collaborations were carried out by scientists in the same physical location-the Manhattan Project of the 1940s, for example, involved thousands of scientists gathered on a remote plateau in Los Alamos, New Mexico. Today, information and communication technologies allow cooperation among scientists from far-flung institutions and different disciplines. Scientific Collaboration on the Internet provides both broad and in-depth views of how new technology is enabling novel kinds of science and engineering collaboration. The book offers commentary from notable experts in the field along with case studies of large-scale collaborative projects, past and ongoing. The projects described range from the development of a national virtual observatory for astronomical research to a National Institutes of Health funding program for major multi-laboratory medical research; from the deployment of a cyberinfrastructure to connect experts in earthquake engineering to partnerships between developed and developing countries in AIDS research. The chapter authors speak frankly about the problems these projects encountered as well as the successes they achieved. The book strikes a useful balance between presenting the real stories of collaborations and developing a scientific approach to conceiving, designing, implementing, and evaluating such projects. It points to a future of scientific collaborations that build successfully on aspects from multiple disciplines. Contributors Mark S. Ackerman, Paul Avery, Matthew Bietz, Jeremy P. Birnholtz, Nathan Bos, Geoffrey C. Bowker, Randal Butler, David Conz, Eric Cook, Dan Cooney, Jonathon Cummings, Erik Dahl, Mark Ellisman, Ixchel Faniel, Thomas A. Finholt, Ian Foster, Jeffrey S. Grethe, Edward J. Hackett, Robert J. Hanisch, Libby Hemphill, Tony Hey, Erik C. Hofer, Mark James, Carl Kessleman, Sara Kiesler, Timothy L. Killeen, Airong Luo, Kelly L. Maglaughlin, Doru Marcusiu, Shawn McKee, William K. Michener, James D. Myers, Marsha Naidoo, Michael Nentwich, Gary M. Olson, Judith S. Olson, James Onken, Andrew Parker, John N. Parker, Mary Puetz, David Ribes, Kathleen Ricker, Diana Rhoten, Michael E. Rogers, Titus Schleyer, Diane H. Sonnenwald, B. F. Spencer, Jr., Stephanie D. Teasley, Anne Trefethen, Robert B. Waide, Mary C. Whitton, William Wulf, Jason Yerkie, Ann Zimmerman
For students, DIY hobbyists, and science buffs, who can no longer get real chemistry sets, this one-of-a-kind guide explains how to set up and use a home chemistry lab, with step-by-step instructions for conducting experiments in basic chemistry - not just to make pretty colors and stinky smells, but to learn how to do real lab work: purify alcohol by distillation; produce hydrogen and oxygen gas by electrolysis; smelt metallic copper from copper ore you make yourself; analyze the makeup of seawater, bone, and other common substances; synthesize oil of wintergreen from aspirin and rayon fiber from paper; perform forensics tests for fingerprints, blood, drugs, and poisons; and much more.From the 1930s through the 1970s, chemistry sets were among the most popular Christmas gifts, selling in the millions. But two decades ago, real chemistry sets began to disappear as manufacturers and retailers became concerned about liability. The Illustrated Guide to Home Chemistry Experiments steps up to the plate with lessons on how to equip your home chemistry lab, master laboratory skills, and work safely in your lab.The bulk of this book consists of 17 hands-on chapters that include multiple laboratory sessions on the following topics: Separating Mixtures; Solubility and Solutions; Colligative Properties of Solutions; Introduction to Chemical Reactions and Stoichiometry; Reduction-Oxidation (Redox) Reactions; Acid-Base Chemistry; Chemical Kinetics; Chemical Equilibrium and Le Chatelier's Principle; Gas Chemistry; Thermochemistry and Calorimetry; Electrochemistry; Photochemistry; Colloids and Suspensions; Qualitative Analysis; Quantitative Analysis; Synthesis of Useful Compounds; and Forensic Chemistry. With plenty of full-color illustrations and photos, Illustrated Guide to Home Chemistry Experiments offers introductory level sessions suitable for a middle school or first-year high school chemistry laboratory course, and more advanced sessions suitable for students who intend to take the College Board Advanced Placement (AP) Chemistry exam. A student who completes all of the laboratories in this book will have done the equivalent of two full years of high school chemistry lab work or a first-year college general chemistry laboratory course. This hands-on introduction to real chemistry - using real equipment, real chemicals, and real quantitative experiments - is ideal for the many thousands of young people and adults who want to experience the magic of chemistry.
Devoted to novel optical measurement techniques that are applied both in industry and life sciences, this book contributes a fresh perspective on the development of modern optical sensors. These sensors are often essential in detecting and controlling parameters that are important for both industrial and biomedical applications. The book provides easy access for beginners wishing to gain familiarity with the innovations of modern optics.
Annual Reports in Computational Chemistry is a new periodical providing timely and critical reviews of important topics in computational chemistry as applied to all chemical disciplines. Topics covered include quantum chemistry, molecular mechanics, force fields, chemical education, and applications in academic and industrial settings. Each volume is organized into (thematic) sections with contributions written by experts. Focusing on the most recent literature and advances in the field, each article covers a specific topic of importance to computational chemists. Annual Reports in Computational Chemistry is a 'must' for researchers and students wishing to stay up-to-date on current developments in computational chemistry. In Volume 3, topics covered include Simulation Methodologies (Carlos Simmerling), Biological and Biophysical Applications (Heather Carlson), Chemical Education (Theresa Zielinski), Materials and Polymers (Jeffry Madura), Quantum Chemistry (T. Daniel Crawford), and Emerging Technologies (Wendy Cornell). With this volume we extend the practice of cumulative indexing of both the current and past editions in order to provide easy identification of past reports.