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This third edition of Design of Experiments for Engineers and Scientists adds to the tried and trusted tools that were successful in so many engineering organizations with new coverage of design of experiments (DoE) in the service sector. Case studies are updated throughout, and new ones are added on dentistry, higher education, and utilities. Although many books have been written on DoE for statisticians, this book overcomes the challenges a wider audience faces in using statistics by using easy-to-read graphical tools. Readers will find the concepts in this book both familiar and easy to understand, and users will soon be able to apply them in their work or research. This classic book is essential reading for engineers and scientists from all disciplines tackling all kinds of product and process quality problems and will be an ideal resource for students of this topic.

Experimental design. --- Research, Industrial. --- Plan d'expérience. --- Recherche industrielle. --- Experimental design --- Research, Industrial --- Scientific research.

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While there are many books available on statistical analysis of data from experiments, there is significantly less available on the design, development, and actual conduct of the experiments. Laboratory Experiments in the Social Sciences summarizes how to design and conduct scientifically sound experiments, be they from surveys, interviews, observations, or experimental methods. The book encompasses how to collect reliable data, the appropriate uses of different methods, and how to avoid or resolve common problems in experimental research. Case study examples illustrate how multiple

Social sciences --- Experimental design. --- Experiments. --- Sciences sociales --- Plan d'expérience --- Expériences. --- Plan d'expérience --- Expériences.

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Experimental design --- Plan d'expérience --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Statistics --- Analysis of means --- Analysis of variance --- Experiments --- Methodology --- Experimental design. --- Plan d'expérience

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This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available information can be used to extract the clearest answers to many questions. The principles are illustrated with a wide range of examples drawn from real experiments in medicine, industry, agriculture and many experimental disciplines. Numerous exercises are given to help the reader practise techniques and to appreciate the difference that good design can make to an experimental research project. Based on Roger Mead's excellent Design of Experiments, this new edition is thoroughly revised and updated to include modern methods relevant to applications in industry, engineering and modern biology. It also contains seven new chapters on contemporary topics, including restricted randomisation and fractional replication.

Mathematical statistics --- Statistics --- Experimental design. --- Statistique --- Plan d'expérience --- Experimental design --- Mathematics --- Plan d'expérience --- Statistical decision. --- Decision problems --- Game theory --- Operations research --- Management science --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Analysis of means --- Analysis of variance --- Experiments --- Methodology --- Research design

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This book should be on the shelf of every practising statistician who designs experiments. Good design considers units and treatments first, and then allocates treatments to units. It does not choose from a menu of named designs. This approach requires a notation for units that does not depend on the treatments applied. Most structure on the set of observational units, or on the set of treatments, can be defined by factors. This book develops a coherent framework for thinking about factors and their relationships, including the use of Hasse diagrams. These are used to elucidate structure, calculate degrees of freedom and allocate treatment subspaces to appropriate strata. Based on a one-term course the author has taught since 1989, the book is 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.

Experimental design --- Plan d'expérience --- Plan d'expérience --- Experimental design. --- Mathematical statistics. --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Design of experiments --- Statistical design --- Mathematical optimization --- Research --- Science --- Statistical decision --- Analysis of means --- Analysis of variance --- Statistical methods --- Experiments --- Methodology