Author: Johannes Ledolter
Publisher:
ISBN: 9780138005672
Category : Engineering
Languages : en
Pages : 591
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Book Description
This hugely anticipated revision has held true to its core strengths, while bringing the book fully up to date with modern engineering statistics. Written by two leading statisticians, Statistics for Engineers and Physical Scientists, Third Edition, provides the necessary bridge between basic statistical theory and interesting applications. Students solve the same problems that engineers and scientists face, and have the opportunity to analyze real data sets. Larger-scale projects are a unique feature of this book, which let students analyze and interpret real data, while also encouraging them to conduct their own studies and compare approaches and results. This book assumes a calculus background. It is appropriate for undergraduate and graduate engineering or physical science courses or for students taking an introductory course applied statistics.
Author: R.Russell Rhinehart
Publisher: Routledge
ISBN: 1351466100
Category : Mathematics
Languages : en
Pages : 481
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Book Description
Originally published in 1991. Textbook on the understanding and application of statistical procedures to engineering problems, for practicing engineers who once had an introductory course in statistics, but haven't used the techniques in a long time.
Author: David M. Levine
Publisher: Pearson
ISBN:
Category : Business & Economics
Languages : en
Pages : 746
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Book Description
For courses in Probability and Statistics. This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.
Author: William Cyrus Navidi
Publisher: College Ie Overruns
ISBN: 9780070166974
Category : Engineering
Languages : en
Pages : 582
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Book Description
Principles of Statistics for Engineers and Scientists offers the same crystal clear presentation of applied statistics as Bill Navidi's Statistics for Engineers and Scientists text, in a manner especially designed for the needs of a one-semester course that is focused on applications. By presenting ideas in the context of real-world data sets and with plentiful examples of computer output, the book is great for motivating students to understand the importance of statistics in their careers and their lives. The text features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly and the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.
Author: William Cyrus Navidi
Publisher: McGraw-Hill
ISBN:
Category : Mathematics
Languages : en
Pages : 936
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Book Description
Author: Scott A. Pardo
Publisher: Springer
ISBN: 3319327682
Category : Mathematics
Languages : en
Pages : 255
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Book Description
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.
Author: William M. Mendenhall
Publisher: CRC Press
ISBN: 1498731856
Category : Mathematics
Languages : en
Pages : 458
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Book Description
A companion to Mendenhall and Sincich’s Statistics for Engineering and the Sciences, Sixth Edition, this student resource offers full solutions to all of the odd-numbered exercises.
Author: Rupert G. Miller, Jr.
Publisher: CRC Press
ISBN: 9780412070112
Category : Mathematics
Languages : en
Pages : 340
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Book Description
Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator. This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests. Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.
Author: Steven L. Brunton
Publisher: Cambridge University Press
ISBN: 1009098489
Category : Computers
Languages : en
Pages : 615
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Book Description
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author: Narayanaswamy Balakrishnan
Publisher: Wiley
ISBN: 9780470405086
Category : Mathematics
Languages : en
Pages : 0
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Book Description
Inspired by the Encyclopedia of Statistical Sciences, Second Edition (ESS2e), this volume presents a concise, well-rounded focus on the statistical concepts and applications that are essential for understanding gathered data in the fields of engineering, quality control, and the physical sciences. The book successfully upholds the goals of ESS2e by combining both previously-published and newly developed contributions written by over 100 leading academics, researchers, and practitioner in a comprehensive, approachable format. The result is a succinct reference that unveils modern, cutting-edge approaches to acquiring and analyzing data across diverse subject areas within these three disciplines, including operations research, chemistry, physics, the earth sciences, electrical engineering, and quality assurance. In addition, techniques related to survey methodology, computational statistics, and operations research are discussed, where applicable. Topics of coverage include: optimal and stochastic control, artificial intelligence, quantum mechanics, and fractals.
