Author: John Lawson
Publisher: CRC Press
ISBN: 1466512180
Category : Business & Economics
Languages : en
Pages : 445
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Book Description
Every technical investigation involving trial-and-error experimentation embodies a strategy for deciding what experiments to perform, when to quit, and how to interpret the data. This handbook presents several statistically derived strategies which are more efficient than any intuitive approach and will get the investigator to their goal with the fewest experiments, give the greatest degree of reliability to their conclusions, and keep the risk of overlooking something of practical importance to a minimum. Features: Provides a comprehensive desk reference on experimental design that will be useful to practitioners without extensive statistical knowledge Features a review of the necessary statistical prerequisites Presents a set of tables that allow readers to quickly access various experimental designs Includes a roadmap for where and when to use various experimental design strategies Shows compelling examples of each method discussed Illustrates how to reproduce results using several popular software packages on a companion web site Following the outlines and examples in this book should quickly allow a working professional or student to select the appropriate experimental design for a research problem at hand, follow the design to conduct the experiments, and analyze and interpret the resulting data. John Lawson and John Erjavec have a combined 25 years of industrial experience and over 40 years of academic experience. They have taught this material to numerous practicing engineers and scientists as well as undergraduate and graduate students.
Author: Les Kirkup
Publisher: Cambridge University Press
ISBN: 1108418465
Category : Science
Languages : en
Pages : 239
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Book Description
An overview of experimental methods providing practical advice to students seeking guidance with their experimental work.
Author: Les Kirkup
Publisher: Wiley
ISBN: 9780471335795
Category : Science
Languages : en
Pages : 216
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Book Description
This concise and easy to read text introduces first year students to the analysis and presentation of experimental data. Written for students taking introductory physics courses at tertiary level, Experimental Methods will be a vital resource for all students involved in experimental or laboratory work. It will be equally useful for other quantitative subjects such as chemistry, engineering and geology. Topics of fundamental importance such as keeping a laboratory notebook, analysing experimental data and report writing are often dealt with in separate texts. This book integrates these topics and provides many of the tools that students will need at first year level and beyond.
Author: John Lawson
Publisher: CRC Press
ISBN: 1000336557
Category : Technology & Engineering
Languages : en
Pages : 299
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Book Description
An Introduction to Acceptance Sampling and SPC with R is an introduction to statistical methods used in monitoring, controlling and improving quality. Topics covered include acceptance sampling; Shewhart control charts for Phase I studies; graphical and statistical tools for discovering and eliminating the cause of out-of-control-conditions; Cusum and EWMA control charts for Phase II process monitoring; and the design and analysis of experiments for process troubleshooting and discovering ways to improve process output. Origins of statistical quality control and the technical topics presented in the remainder of the book are those recommended in the ANSI/ASQ/ISO guidelines and standards for industry. The final chapter ties everything together by discussing modern management philosophies that encourage the use of the technical methods presented earlier. In the modern world sampling plans and the statistical calculations used in statistical quality control are done with the help of computers. As an open source high-level programming language with flexible graphical output options, R runs on Windows, Mac and Linux operating systems, and has add-on packages that equal or exceed the capability of commercial software for statistical methods used in quality control. In this book, we will focus on several R packages. In addition to demonstrating how to use R for acceptance sampling and control charts, this book will concentrate on how the use of these specific tools can lead to quality improvements both within a company and within their supplier companies. This would be a suitable book for a one-semester undergraduate course emphasizing statistical quality control for engineering majors (such as manufacturing engineering or industrial engineering), or a supplemental text for a graduate engineering course that included quality control topics.
Author: Claes Wohlin
Publisher: Springer Science & Business Media
ISBN: 3642290442
Category : Computers
Languages : en
Pages : 249
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Book Description
Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools. The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors’ book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a “cookbook” when evaluating new methods or techniques before implementing them in their organization.
Author: John Lawson
Publisher: Chapman and Hall/CRC
ISBN: 9781439868133
Category : Mathematics
Languages : en
Pages : 0
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Book Description
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.
Author: Valentim R. Alferes
Publisher: SAGE
ISBN: 1452202923
Category : Psychology
Languages : en
Pages : 209
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Book Description
This text provides a conceptual systematization and a practical tool for the randomization of between-subjects and within-subjects experimental designs.
Author: W. Newton Suter
Publisher: SAGE
ISBN: 1412995736
Category : Education
Languages : en
Pages : 529
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Book Description
W. Newton Suter argues that what is important in a changing education landscape is the ability to think clearly about research methods, reason through complex problems and evaluate published research. He explains how to evaluate data and establish its relevance.
Author: Arthur Pyster
Publisher: John Wiley & Sons
ISBN: 1119412161
Category : Technology & Engineering
Languages : en
Pages : 265
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Book Description
A guide that explores what enables systems engineers to be effective in their profession and reveals how organizations can help them attain success The Paradoxical Mindset of Systems Engineers offers an in-depth look at the proficiencies and personal qualities effective systems engineers require and the positions they should seek for successful careers. The book also gives employers practical strategies and tools to evaluate their systems engineers and advance them to higher performance. The authors explore why systems engineers are uncommon and how they can assess, improve, and cleverly leverage their uncommon strengths. These insights for being an ever more effective systems engineer apply equally well to classic engineers and project managers who secondarily do some systems engineering. The authors have written a guide to help systems engineers embrace the values that are most important to themselves and their organizations. Solidly based on interviews with over 350 systems engineers, classic engineers, and managers as well as detailed written career descriptions from 2500 systems engineers — The Paradoxical Mindset of Systems Engineers identifies behavioral patterns that effective systems engineers use to achieve success. This important resource: Offers aspiring systems engineers practical methods for success that are built on extensive empirical evidence and underlying theory Shows systems engineers how to visually document their relative strengths and weaknesses, map out their careers, and compare themselves to the best in their organizations – a rich set of tools for individuals, mentors, and organizations Offers practical guidance to managers and executives who lead systems engineering workforce improvement initiatives Written for systems engineers, their managers, business executives, those who do some systems engineering but primarily identify with other professions, as well as HR professionals, The Paradoxical Mindset of Systems Engineers offers the most comprehensive career guidance in the field available today.
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309486165
Category : Science
Languages : en
Pages : 257
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Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
