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Design and Analysis of Experiments with R

Author: John Lawson

Publisher: Chapman and Hall/CRC

Published: 2014-12-17

Total Pages: 0

ISBN-13: 9781439868133

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results. Drawing on his many years of working in the pharmaceutical, agricultural, industrial chemicals, and machinery industries, the author teaches students how to: Make an appropriate design choice based on the objectives of a research project Create a design and perform an experiment Interpret the results of computer data analysis The book emphasizes the connection among the experimental units, the way treatments are randomized to experimental units, and the proper error term for data analysis. R code is used to create and analyze all the example experiments. The code examples from the text are available for download on the author’s website, enabling students to duplicate all the designs and data analysis. Intended for a one-semester or two-quarter course on experimental design, this text covers classical ideas in experimental design as well as the latest research topics. It gives students practical guidance on using R to analyze experimental data.

Design and Analysis of Experiments with R

Author: John Lawson

Publisher: CRC Press

Published: 2014-12-17

Total Pages: 629

ISBN-13: 1498728480

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Design and Analysis of Experiments

Author: Douglas C. Montgomery

Publisher: Wiley

Published: 2005

Total Pages: 0

ISBN-13: 9780471661597

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This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.

A First Course in Design and Analysis of Experiments

Author: Gary W. Oehlert

Publisher:

Published: 2010

Total Pages: 659

ISBN-13:

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"Oehlert’s text is suitable for either a service course for non-statistics graduate students or for statistics majors. Unlike most texts for the one-term grad/upper level course on experimental design, Oehlert’s new book offers a superb balance of both analysis and design, presenting three practical themes to students: when to use various designs; how to analyze the results; how to recognize various design options. Also, unlike other older texts, the book is fully oriented toward the use of statistical software in analyzing experiments"--Publisher's description.

Handbook of Design and Analysis of Experiments

Author: Angela Dean

Publisher: CRC Press

Published: 2015-06-26

Total Pages: 946

ISBN-13: 146650434X

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This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.

Design and Analysis of Time Series Experiments

Author: Richard McCleary

Publisher: Oxford University Press

Published: 2017

Total Pages: 393

ISBN-13: 0190661569

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Design and Analysis of Time Series Experiments presents the elements of statistical time series analysis while also addressing recent developments in research design and causal modeling. A distinguishing feature of the book is its integration of design and analysis of time series experiments. Drawing examples from criminology, economics, education, pharmacology, public policy, program evaluation, public health, and psychology, Design and Analysis of Time Series Experiments is addressed to researchers and graduate students in a wide range of behavioral, biomedical and social sciences. Readers learn not only how-to skills but, also the underlying rationales for the design features and the analytical methods. ARIMA algebra, Box-Jenkins-Tiao models and model-building strategies, forecasting, and Box-Tiao impact models are developed in separate chapters. The presentation of the models and model-building assumes only exposure to an introductory statistics course, with more difficult mathematical material relegated to appendices. Separate chapters cover threats to statistical conclusion validity, internal validity, construct validity, and external validity with an emphasis on how these threats arise in time series experiments. Design structures for controlling the threats are presented and illustrated through examples. The chapters on statistical conclusion validity and internal validity introduce Bayesian methods, counterfactual causality and synthetic control group designs. Building on the earlier of the authors, Design and Analysis of Time Series Experiments includes more recent developments in modeling, and considers design issues in greater detail than any existing work. Additionally, the book appeals to those who want to conduct or interpret time series experiments, as well as to those interested in research designs for causal inference.--

Optimal Experimental Design with R

Author: Dieter Rasch

Publisher: CRC Press

Published: 2011-05-18

Total Pages: 345

ISBN-13: 1439816980

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Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experi

The Design and Analysis of Computer Experiments

Author: Thomas J. Santner

Publisher: Springer

Published: 2019-01-08

Total Pages: 436

ISBN-13: 1493988476

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This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners

Design of Experiments in Chemical Engineering

Author: Zivorad R. Lazic

Publisher: John Wiley & Sons

Published: 2006-03-06

Total Pages: 620

ISBN-13: 3527604596

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While existing books related to DOE are focused either on process or mixture factors or analyze specific tools from DOE science, this text is structured both horizontally and vertically, covering the three most common objectives of any experimental research: * screening designs * mathematical modeling, and * optimization. Written in a simple and lively manner and backed by current chemical product studies from all around the world, the book elucidates basic concepts of statistical methods, experiment design and optimization techniques as applied to chemistry and chemical engineering. Throughout, the focus is on unifying the theory and methodology of optimization with well-known statistical and experimental methods. The author draws on his own experience in research and development, resulting in a work that will assist students, scientists and engineers in using the concepts covered here in seeking optimum conditions for a chemical system or process. With 441 tables, 250 diagrams, as well as 200 examples drawn from current chemical product studies, this is an invaluable and convenient source of information for all those involved in process optimization.

Introduction to Design and Analysis of Experiments

Author: George W. Cobb

Publisher: Wiley

Published: 2008-06-10

Total Pages: 0

ISBN-13: 9780470412169

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Introduction to Design and Analysis of Experiments explains how to choose sound and suitable design structures and engages students in understanding the interpretive and constructive natures of data analysis and experimental design. Cobb's approach allows students to build a deep understanding of statistical concepts over time as they analyze and design experiments. The field of statistics is presented as a matrix, rather than a hierarchy, of related concepts. Developed over years of classroom use, this text can be used as an introduction to statistics emphasizing experimental design or as an elementary graduate survey course. Widely praised for its exceptional range of intelligent and creative exercises, and for its large number of examples and data sets, Introduction to Design and Analysis of Experiments--now offered in a convenient paperback format--helps students increase their understanding of the material as they come to see the connections between diverse statistical concepts that arise from the experiments around which the text is built.