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Uncertainty Analysis of Experimental Data with R

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Release : 2017-07-06
Genre : Mathematics
Kind : eBook
Book Rating : 334/5 ( reviews)

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Book Synopsis Uncertainty Analysis of Experimental Data with R by : Benjamin David Shaw

Download or read book Uncertainty Analysis of Experimental Data with R written by Benjamin David Shaw. This book was released on 2017-07-06. 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.

Experimentation and Uncertainty Analysis for Engineers

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Author :
Release : 1989-09-05
Genre : Technology & Engineering
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Experimentation and Uncertainty Analysis for Engineers by : Hugh W. Coleman

Download or read book Experimentation and Uncertainty Analysis for Engineers written by Hugh W. Coleman. This book was released on 1989-09-05. Available in PDF, EPUB and Kindle. Book excerpt: How to apply uncertainty analysis to experimentation. Describes how to incorporate uncertainty analysis into the planning, design, construction, debugging, execution, data analysis, and reporting stages of experimental programs. Estimation and propagation of both precision (random) errors and bias (fixed) errors are considered, as are procedures for handling small samples (which require use of the t-distribution), and practical cases in which bias errors in different variables are correlated. Treatment follows (and explains) the ANSI/ASME Standard on Measurement Uncertainty. Chapters 1 through 4 develop methodology for proper consideration of the uncertainty in measured variables and their propagation into the result of an experimantal program. Chapters 5 through 7 present additional considerations in the design of experiments, and illustrate application of the methods given in earlier chapters.

Uncertainty Analysis of Experimental Data with R

Download Uncertainty Analysis of Experimental Data with R PDF Online Free

Author :
Release : 2017
Genre : Probabilities
Kind : eBook
Book Rating : 715/5 ( reviews)

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Book Synopsis Uncertainty Analysis of Experimental Data with R by : Benjamin D. Shaw

Download or read book Uncertainty Analysis of Experimental Data with R written by Benjamin D. Shaw. This book was released on 2017. 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 UniversityMeasurements 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.?"--Provided by publisher.

Experimental Uncertainty Analysis: A Textbook for Science and Engineering Students

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Author :
Release : 2021-07-06
Genre : Technology & Engineering
Kind : eBook
Book Rating : 321/5 ( reviews)

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Book Synopsis Experimental Uncertainty Analysis: A Textbook for Science and Engineering Students by : Supreet Singh Bahga

Download or read book Experimental Uncertainty Analysis: A Textbook for Science and Engineering Students written by Supreet Singh Bahga. This book was released on 2021-07-06. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainties are inevitable in any experimental measurement. Therefore, it is essential for science and engineering graduates to design and develop reliable experiments and estimate the uncertainty in the measurements. This book describes the methods and application of uncertainty analysis during the planning, data analysis, and reporting stages of an experiment. This book is aimed at postgraduate and advanced undergraduate students of various branches of science and engineering. The book teaches methods for estimating random and systematic uncertainties and combining them to determine the overall uncertainty in a measurement. In addition, the method for propagating measurement uncertainties in the calculated result is discussed. The book also discusses methods of reducing the uncertainties through proper instrumentation, data acquisition, and experiment planning. This book provides detailed background and assumptions underlying the uncertainty analysis techniques for the reader to understand their applicability. Various solved examples are provided to demonstrate the application of the uncertainty analysis techniques. The exercises at the end of the chapters have been chosen carefully to reinforce the concepts discussed in the text.

Experimentation, Validation, and Uncertainty Analysis for Engineers

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Author :
Release : 2018-03-29
Genre : Technology & Engineering
Kind : eBook
Book Rating : 66X/5 ( reviews)

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Book Synopsis Experimentation, Validation, and Uncertainty Analysis for Engineers by : Hugh W. Coleman

Download or read book Experimentation, Validation, and Uncertainty Analysis for Engineers written by Hugh W. Coleman. This book was released on 2018-03-29. Available in PDF, EPUB and Kindle. Book excerpt: Helps engineers and scientists assess and manage uncertainty at all stages of experimentation and validation of simulations Fully updated from its previous edition, Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes expanded coverage and new examples of applying the Monte Carlo Method (MCM) in performing uncertainty analyses. Presenting the current, internationally accepted methodology from ISO, ANSI, and ASME standards for propagating uncertainties using both the MCM and the Taylor Series Method (TSM), it provides a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, debugging, execution, data analysis, and reporting phases of experimental and validation programs. It also illustrates how to use a spreadsheet approach to apply the MCM and the TSM, based on the authors’ experience in applying uncertainty analysis in complex, large-scale testing of real engineering systems. Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes examples throughout, contains end of chapter problems, and is accompanied by the authors’ website www.uncertainty-analysis.com. Guides readers through all aspects of experimentation, validation, and uncertainty analysis Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis Includes complete new examples throughout Features workable problems at the end of chapters Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition is an ideal text and guide for researchers, engineers, and graduate and senior undergraduate students in engineering and science disciplines. Knowledge of the material in this Fourth Edition is a must for those involved in executing or managing experimental programs or validating models and simulations.

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