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Data Analysis For Scientists And Engineers


Data Analysis For Scientists And Engineers
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Data Analysis For Scientists And Engineers


Data Analysis For Scientists And Engineers
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Author : Edward L. Robinson
language : en
Publisher: Princeton University Press
Release Date : 2016-09-20

Data Analysis For Scientists And Engineers written by Edward L. Robinson and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-20 with Science categories.


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)



Data Analysis For Scientists And Engineers


Data Analysis For Scientists And Engineers
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Author : Stuart L. Meyer
language : en
Publisher: John Wiley & Sons
Release Date : 1975

Data Analysis For Scientists And Engineers written by Stuart L. Meyer and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 1975 with Mathematics categories.


Introduction to scientific measurement; Introduction to graphical techniques and curve fitting; Probability; Some probability distributions and applications; Statitical inference.



Data Analysis


Data Analysis
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Author : Siegmund Brandt
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-02-14

Data Analysis written by Siegmund Brandt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-14 with Science categories.


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.



Basic Environmental Data Analysis For Scientists And Engineers


Basic Environmental Data Analysis For Scientists And Engineers
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Author : Ralph R.B. Von Frese
language : en
Publisher: CRC Press
Release Date : 2019-11-22

Basic Environmental Data Analysis For Scientists And Engineers written by Ralph R.B. Von Frese and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-22 with Mathematics categories.


Classroom tested and the result of over 30 years of teaching and research, this textbook is an invaluable tool for undergraduate and graduate data analysis courses in environmental sciences and engineering. It is also a useful reference on modern digital data analysis for the extensive and growing community of Earth scientists and engineers. Basic Environmental Data Analysis for Scientists and Engineers introduces practical concepts of modern digital data analysis and graphics, including numerical/graphical calculus, measurement units and dimensional analysis, error propagation and statistics, and least squares data modeling. It emphasizes array-based or matrix inversion and spectral analysis using the fast Fourier transform (FFT) that dominates modern data analysis. Divided into two parts, this comprehensive hands-on textbook is excellent for exploring data analysis principles and practice using MATLAB®, Mathematica, Mathcad, and other modern equation solving software. Part I, for beginning undergraduate students, introduces the basic approaches for quantifying data variations in terms of environmental parameters. These approaches emphasize uses of the data array or matrix, which is the fundamental data and mathematical processing format of modern electronic computing. Part II, for advanced undergraduate and beginning graduate students, extends the inverse problem to least squares solutions involving more than two unknowns. Features: Offers a uniquely practical guide for making students proficient in modern electronic data analysis and graphics Includes topics that are not explained in any existing textbook on environmental data analysis Data analysis topics are very well organized into a two-semester course that meets general education curriculum requirements in science and engineering Facilitates learning by beginning each chapter with an ‘Overview’ section highlighting the topics covered, and ending it with a ‘Key Concepts’ section summarizing the main technical details that the reader should have acquired Indexes many numerical examples for ready access in the classroom or other venues serviced by electronic equation solvers like MATLAB®, Mathematica, Mathcad, etc. Offers supplemental exercises and materials to enhance understanding the principles and practice of modern data analysis



Statistics And Data Analysis For Engineers And Scientists


Statistics And Data Analysis For Engineers And Scientists
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Author : Tanvir Mustafy
language : en
Publisher: Springer Nature
Release Date : 2024-02-11

Statistics And Data Analysis For Engineers And Scientists written by Tanvir Mustafy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-11 with Technology & Engineering categories.


This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs—Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses, and apply them to their research or professional fields. The book also includes worked examples of practical problems. The primary focus behind designing these examples is understanding the concepts of data analysis and how it can solve problems. The chapters include practice exercises to assist users in enhancing their skills to execute statistical analysis calculations using software instead of relying on tables for probabilities and percentiles in the present world.



Applied Data Analysis And Modeling For Energy Engineers And Scientists


Applied Data Analysis And Modeling For Energy Engineers And Scientists
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Author : T. Agami Reddy
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-09

Applied Data Analysis And Modeling For Energy Engineers And Scientists written by T. Agami Reddy and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-09 with Technology & Engineering categories.


Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.



Basic Experimental Strategies And Data Analysis For Science And Engineering


Basic Experimental Strategies And Data Analysis For Science And Engineering
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Author : John Lawson
language : en
Publisher: CRC Press
Release Date : 2016-11-03

Basic Experimental Strategies And Data Analysis For Science And Engineering written by John Lawson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Business & Economics categories.


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.



The Data Analysis Briefbook


The Data Analysis Briefbook
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Author : Rudolf K. Bock
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14

The Data Analysis Briefbook written by Rudolf K. Bock and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Science categories.


This BriefBook is a much extended glossary or a much condensed handbook, depending on the way one looks at it. In encyclopedic format, it covers subjects in statistics, computing, analysis, and related fields, resulting in a book that is both an introduction and a reference for scientists and engineers, especially experimental physicists dealing with data analysis.



Empirical Modeling And Data Analysis For Engineers And Applied Scientists


Empirical Modeling And Data Analysis For Engineers And Applied Scientists
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Author : Scott A. Pardo
language : en
Publisher: Springer
Release Date : 2016-07-19

Empirical Modeling And Data Analysis For Engineers And Applied Scientists written by Scott A. Pardo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-19 with Mathematics categories.


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.



Introduction To Environmental Data Analysis For Scientists And Engineers


Introduction To Environmental Data Analysis For Scientists And Engineers
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Author : Ralph R B Von Frese
language : en
Publisher: CRC Press
Release Date : 2019

Introduction To Environmental Data Analysis For Scientists And Engineers written by Ralph R B Von Frese and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Environmental sciences categories.


This hands-on textbook introduces basic concepts of modern digital data analysis and graphics including numerical/graphical calculus, measurement units and dimensional analysis, non-statistical and statistical error analysis, etc. It emphasizes array-based or matrix inversion and spectral analysis using the fast Fourier transform (FFT) that dominates modern data analysis. It is comprehensive and better suited for student exploration efforts using modern equation solving software like MATLAB®, Mathematica, MathCad, etc. This textbook is focused on the basic mathematical methods, which distinguishes it from the rest of software focused textbooks.