Download or read book Basic Experimental Strategies and Data Analysis for Science and Engineering written by John Lawson and published by CRC Press. This book was released on 2016-11-03 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Experimental Methods for Science and Engineering Students written by Les Kirkup and published by Cambridge University Press. This book was released on 2019-09-05 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of experimental methods providing practical advice to students seeking guidance with their experimental work.

Download or read book Statistical Design and Analysis of Experiments written by Robert L. Mason and published by John Wiley & Sons. This book was released on 2003-05-09 with total page 752 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results. Features numerous examples using actual engineering and scientific studies. Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions. Deep and concentrated experimental design coverage, with equivalent but separate emphasis on the analysis of data from the various designs. Topics can be implemented by practitioners and do not require a high level of training in statistics. New edition includes new and updated material and computer output.

Download or read book Data Analysis for Scientists and Engineers written by Edward L. Robinson and published by Princeton University Press. This book was released on 2016-09-20 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix. Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. In-depth discussion of data analysis for scientists and engineers Coverage of both frequentist and Bayesian approaches to data analysis Extensive look at analysis techniques for time-series data and images Detailed exploration of linear and nonlinear modeling of data Emphasis on error analysis Instructor's manual (available only to professors)

Download or read book Data Analysis written by Siegmund Brandt and published by Springer. This book was released on 2017-04-30 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.

Download or read book Measurement and Data Analysis for Engineering and Science written by Patrick F. Dunn and published by McGraw-Hill Education. This book was released on 2004-07-01 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Website includes solutions to all chapter problems, information on lab set-up and implementation, MATLAB resources and m-files, links to professional & association websites, and other student learning resources. Dunn's Experimental Methods & Measurement for Engineers offers an up-date-date, practical approach to learning and implementing lab skills, technical reporting, and data analysis. The first three chapters of the text cover the basics--experimental methods, units & significant figures, technical communications and basic electronics. Hardware issues are then presented, with a focus on measurement systems, and calibration & response. The final chapters deal with data analysis, with an overview of basic probability & statistics, uncertainty analysis, signal characteristics, and digital signal analysis. Following the text chapters, a full laboratory manual, with an introduction and twelve full lab experiments, is included. This gives users a chance to put their basic skills to work in actual engineering experiments, which are taken from a variety of engineering subject areas. Throughout the book computer techniques are discussed, and specific MATLAB applications are included, for problem modeling, exploration and solution. MATLAB "sidebars" are used to present MATLAB, and associated m-files are provided on the Book Website. This site will also include problem solutions and lab discussions for instructors, PowerPoint slides of key text figures, links to professional and association websites, and other student learning resources

Download or read book Planning Construction and Statistical Analysis of Comparative Experiments written by Francis G. Giesbrecht and published by John Wiley & Sons. This book was released on 2011-09-26 with total page 693 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable guide to conducting experiments and analyzing dataacross a wide range of applications Experimental design is an important component of the scientificmethod. This book provides guidance on planning efficientinvestigations. It compiles designs for a wide range ofexperimental situations not previously found in accessible form.Focusing on applications in the physical, engineering, biological,and social sciences, Planning, Construction, and StatisticalAnalysis of Comparative Experiments is a valuable guide todesigning experiments and correctly analyzing and interpreting theresults. The authors draw on their years of experience in theclassroom and as statistical consultants to research programs oncampus, in government, and in industry. The object is always tostrike the right balance between mathematical necessities andpractical constraints. Serving both as a textbook for students of intermediatestatistics and a hands-on reference for active researchers, thetext includes: A wide range of applications, including agricultural sciences,animal and biomedical sciences, and industrial engineeringstudies General formulas for estimation and hypothesis testing,presented in a unified and simplified manner Guidelines for evaluating the power and efficiency of designsthat are not perfectly balanced New developments in the design of fractional factorials withnon-prime numbers of levels in mixed-level fractionalfactorials Detailed coverage on the construction of plans and therelationship among categories of designs Thorough coverage of balanced, lattice, cyclic, and alphadesigns Strategies for sequences of fractional factorials Data sets and SAS® code on a companion web site An ideal handbook for the investigator planning a researchprogram, the text comes complete with detailed plans of experimentsand alternative approaches for added flexibility.

Download or read book Measurement and Data Analysis for Engineering and Science Second Edition written by Patrick F. Dunn and published by CRC Press. This book was released on 2010-01-05 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting the fundamental tools of experimentation that are currently used by engineers and scientists, Measurement and Data Analysis for Engineering and Science, Second Edition covers the basics of experimentation, hardware of experiments, and methods of data analysis. It also offers historical perspectives throughout. Updating and reorganizing its popular predecessor, this second edition makes the text much easier to follow and enhances the presentation with electronic material. New to the Second Edition Order of chapters now reflects the sequence of topics usually included in an undergraduate course Asterisked sections denote material not typically covered formally during lecture in an introductory undergraduate course More than 150 new problems, bringing the total to over 420 problems Supplementary website that provides unit conversions, learning objectives, review crossword puzzles and solutions, differential equation derivations, laboratory exercise descriptions, MATLAB® sidebars with M-files, and homework data files Thorough and up to date, this edition continues to help students gain a fundamental understanding of the tools of experimentation. It discusses basic concepts related to experiments, measurement system components and responses, data analysis, and effective communication of experimental findings. Ancillary materials for instructors are available on a CD-ROM and a solutions manual is available for qualifying instructors. More data available on www.nd.edu/~pdunn/www.text/measurements.html

Download or read book Analysis and Presentation of Experimental Results written by Costas Christodoulides and published by Springer. This book was released on 2017-06-14 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended as a guide to the analysis and presentation of experimental results. It develops various techniques for the numerical processing of experimental data, using basic statistical methods and the theory of errors. After presenting basic theoretical concepts, the book describes the methods by which the results can be presented, both numerically and graphically. The book is divided into three parts, of roughly equal length, addressing the theory, the analysis of data, and the presentation of results. Examples are given and problems are solved using the Excel, Origin, Python and R software packages. In addition, programs in all four languages are made available to readers, allowing them to use them in analyzing and presenting the results of their own experiments. Subjects are treated at a level appropriate for undergraduate students in the natural sciences, but this book should also appeal to anyone whose work involves dealing with experimental results.

Download or read book Empirical Modeling and Data Analysis for Engineers and Applied Scientists written by Scott A. Pardo and published by Springer. This book was released on 2016-07-19 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook teaches advanced undergraduate and first-year graduate students in Engineering and Applied Sciences to gather and analyze empirical observations (data) in order to aid in making design decisions. While science is about discovery, the primary paradigm of engineering and "applied science" is design. Scientists are in the discovery business and want, in general, to understand the natural world rather than to alter it. In contrast, engineers and applied scientists design products, processes, and solutions to problems. That said, statistics, as a discipline, is mostly oriented toward the discovery paradigm. Young engineers come out of their degree programs having taken courses such as "Statistics for Engineers and Scientists" without any clear idea as to how they can use statistical methods to help them design products or processes. Many seem to think that statistics is only useful for demonstrating that a device or process actually does what it was designed to do. Statistics courses emphasize creating predictive or classification models - predicting nature or classifying individuals, and statistics is often used to prove or disprove phenomena as opposed to aiding in the design of a product or process. In industry however, Chemical Engineers use designed experiments to optimize petroleum extraction; Manufacturing Engineers use experimental data to optimize machine operation; Industrial Engineers might use data to determine the optimal number of operators required in a manual assembly process. This text teaches engineering and applied science students to incorporate empirical investigation into such design processes. Much of the discussion in this book is about models, not whether the models truly represent reality but whether they adequately represent reality with respect to the problems at hand; many ideas focus on how to gather data in the most efficient way possible to construct adequate models. Includes chapters on subjects not often seen together in a single text (e.g., measurement systems, mixture experiments, logistic regression, Taguchi methods, simulation) Techniques and concepts introduced present a wide variety of design situations familiar to engineers and applied scientists and inspire incorporation of experimentation and empirical investigation into the design process. Software is integrally linked to statistical analyses with fully worked examples in each chapter; fully worked using several packages: SAS, R, JMP, Minitab, and MS Excel - also including discussion questions at the end of each chapter. The fundamental learning objective of this textbook is for the reader to understand how experimental data can be used to make design decisions and to be familiar with the most common types of experimental designs and analysis methods.

Download or read book The Systematic Experiment written by J. C. Gibbings and published by CUP Archive. This book was released on 1986-09-18 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explains how to plan, execute, analyse and write up an experiment. Experimentation is an essential part of science and engineering, being both the basis of discovery in science and an integral part of engineering development. The authors' aim is to provide instruction in how to perform a systematic experiment from its conception and design through to the communication of results. The text opens by laying the ground rules for the planning of an experiment, moving on to a description of measurement techniques and statistical analysis of results. An important feature of the book is the inclusion of a chapter on the interfacing of experimental equipment to microcomputers.

Download or read book Statistics for Experimenters written by George E. P. Box and published by Wiley-Interscience. This book was released on 1978-07-06 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces the philosophy of experimentation and the part that statistics plays in experimentation. Emphasizes the need to develop a capability for statistical thinking by using examples drawn from actual case studies.

Download or read book Design of Experiments for Engineers and Scientists written by Jiju Antony and published by Elsevier. This book was released on 2014-02-22 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tools and techniques used in Design of Experiments (DoE) have been proven successful in meeting the challenge of continuous improvement in many manufacturing organisations over the last two decades. However research has shown that application of this powerful technique in many companies is limited due to a lack of statistical knowledge required for its effective implementation. Although many books have been written on this subject, they are mainly by statisticians, for statisticians and not appropriate for engineers. Design of Experiments for Engineers and Scientists overcomes the problem of statistics by taking a unique approach using graphical tools. The same outcomes and conclusions are reached as through using statistical methods and readers will find the concepts in this book both familiar and easy to understand. This new edition includes a chapter on the role of DoE within Six Sigma methodology and also shows through the use of simple case studies its importance in the service industry. It is essential reading for engineers and scientists from all disciplines tackling all kinds of manufacturing, product and process quality problems and will be an ideal resource for students of this topic. Written in non-statistical language, the book is an essential and accessible text for scientists and engineers who want to learn how to use DoE Explains why teaching DoE techniques in the improvement phase of Six Sigma is an important part of problem solving methodology New edition includes a full chapter on DoE for services as well as case studies illustrating its wider application in the service industry

Download or read book Introductory Statistics for Engineering Experimentation written by Peter R. Nelson and published by Elsevier. This book was released on 2003-09-25 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that "Students must demonstrate a knowledge of the application of statistics to engineering problems." Since most engineering curricula are filled with requirements in their own discipline, they generally do not have time for a traditional two semesters of probability and statistics. Attempts to condense that material into a single semester often results in so much time being spent on probability that the statistics useful for designing and analyzing engineering/scientific experiments is never covered. In developing a one-semester course whose purpose was to introduce engineering/scientific students to the most useful statistical methods, this book was created to satisfy those needs. Provides the statistical design and analysis of engineering experiments & problems Presents a student-friendly approach through providing statistical models for advanced learning techniques Covers essential and useful statistical methods used by engineers and scientists

Download or read book Uncertainty Analysis of Experimental Data with R written by Benjamin David Shaw and published by CRC Press. This book was released on 2017-07-06 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This would be an excellent book for undergraduate, graduate and beyond....The style of writing is easy to read and the author does a good job of adding humor in places. The integration of basic programming in R with the data that is collected for any experiment provides a powerful platform for analysis of data.... having the understanding of data analysis that this book offers will really help researchers examine their data and consider its value from multiple perspectives – and this applies to people who have small AND large data sets alike! This book also helps people use a free and basic software system for processing and plotting simple to complex functions." Michelle Pantoya, Texas Tech University Measurements of quantities that vary in a continuous fashion, e.g., the pressure of a gas, cannot be measured exactly and there will always be some uncertainty with these measured values, so it is vital for researchers to be able to quantify this data. Uncertainty Analysis of Experimental Data with R covers methods for evaluation of uncertainties in experimental data, as well as predictions made using these data, with implementation in R. The books discusses both basic and more complex methods including linear regression, nonlinear regression, and kernel smoothing curve fits, as well as Taylor Series, Monte Carlo and Bayesian approaches. Features: 1. Extensive use of modern open source software (R). 2. Many code examples are provided. 3. The uncertainty analyses conform to accepted professional standards (ASME). 4. The book is self-contained and includes all necessary material including chapters on statistics and programming in R. Benjamin D. Shaw is a professor in the Mechanical and Aerospace Engineering Department at the University of California, Davis. His research interests are primarily in experimental and theoretical aspects of combustion. Along with other courses, he has taught undergraduate and graduate courses on engineering experimentation and uncertainty analysis. He has published widely in archival journals and became an ASME Fellow in 2003.

Download or read book An Introduction to Acceptance Sampling and SPC with R written by John Lawson and published by CRC Press. This book was released on 2021-02-25 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Measurement and Data Analysis for Engineering and Science Third Edition written by Patrick F. Dunn and published by CRC Press. This book was released on 2014-05-23 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: The third edition of Measurement and Data Analysis for Engineering and Science provides an up-to-date approach to presenting the methods of experimentation in science and engineering. Widely adopted by colleges and universities within the U.S. and abroad, this edition has been developed as a modular work to make it more adaptable to different approaches from various schools. This text details current methods and highlights the six fundamental tools required for implementation: planning an experiment, identifying measurement system components, assessing measurement system component performance, setting signal sampling conditions, analyzing experimental results, and reporting experimental results. What’s New in the Third Edition: This latest edition includes a new chapter order that presents a logical sequence of topics in experimentation, from the planning of an experiment to the reporting of the experimental results. It adds a new chapter on sensors and transducers that describes approximately 50 different sensors commonly used in engineering, presents uncertainty analysis in two separate chapters, and provides a problem topic summary in each chapter. New topics include smart measurement systems, focusing on the Arduino® microcontroller and its use in the wireless transmission of data, and MATLAB® and Simulink® programming for microcontrollers. Further topic additions are on the rejection of data outliers, light radiation, calibrations of sensors, comparison of first-order sensor responses, the voltage divider, determining an appropriate sample period, and planning a successful experiment. Measurement and Data Analysis for Engineering and Science also contains more than 100 solved example problems, over 400 homework problems, and provides over 75 MATLAB® Sidebars with accompanying MATLAB M-files, Arduino codes, and data files available for download.