| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230417b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780367241704 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
001.434028553 |
| Item number |
SHA |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Shaw, Benjamin D. |
| 245 ## - TITLE STATEMENT |
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| Title |
Uncertainty analysis of experimental data with R |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
CRC Press, |
| Place of publication, distribution, etc |
2017 |
| Date of publication, distribution, etc |
Boca Raton : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
ix, 195 p. ; |
| Other physical details |
ill., |
| Dimensions |
24 cm |
| 365 ## - TRADE PRICE |
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| Price amount |
2495.00 |
| Price type code |
INR |
| Unit of pricing |
01 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
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.? |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Accept/reject method |
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| Topical term or geographic name as entry element |
Bayesian approach |
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| Topical term or geographic name as entry element |
Confidence interval |
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| Topical term or geographic name as entry element |
Curve fitting technique |
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| Topical term or geographic name as entry element |
Data visualization |
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| Topical term or geographic name as entry element |
Elemental sysmatic error |
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| Topical term or geographic name as entry element |
General linear regression theory |
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| Topical term or geographic name as entry element |
Kernel smoothing methods |
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| Topical term or geographic name as entry element |
Linear regression |
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| Topical term or geographic name as entry element |
Monte Carlo(MC) methods |
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| Topical term or geographic name as entry element |
Nonparametric boot-strapping |
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| Topical term or geographic name as entry element |
Probability density function |
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| Topical term or geographic name as entry element |
Taylor series approach |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Item type |
Books |