Measurement and Data Analysis for Engineering and Science, Third Edition

2014-05-23

PDF Measurement and Data Analysis for Engineering and Science, Third Edition Download

Author: Patrick F. Dunn
Publisher: CRC Press
ISBN: 1466594969
Category : Technology & Engineering
Languages : en
Pages : 634

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.

Measurement, Data Analysis, and Sensor Fundamentals for Engineering and Science

2019-02-20

PDF Measurement, Data Analysis, and Sensor Fundamentals for Engineering and Science Download

Author: Patrick F. Dunn
Publisher: CRC Press
ISBN: 1351991655
Category : Technology & Engineering
Languages : en
Pages : 754

A combination of two texts authored by Patrick Dunn, this set covers sensor technology as well as basic measurement and data analysis subjects, a combination not covered together in other references. Written for junior-level mechanical and aerospace engineering students, the topic coverage allows for flexible approaches to using the combination book in courses. MATLAB® applications are included in all sections of the combination, and concise, applied coverage of sensor technology is offered. Numerous chapter examples and problems are included, with complete solutions available.

Measurement, Data Analysis, and Sensor Fundamentals for Engineering and Science

2019-02-20

PDF Measurement, Data Analysis, and Sensor Fundamentals for Engineering and Science Download

Author: Patrick F. Dunn
Publisher: CRC Press
ISBN: 1439875308
Category : Technology & Engineering
Languages : en
Pages : 734

A combination of two texts authored by Patrick Dunn, this set covers sensor technology as well as basic measurement and data analysis subjects, a combination not covered together in other references. Written for junior-level mechanical and aerospace engineering students, the topic coverage allows for flexible approaches to using the combination book in courses. MATLAB® applications are included in all sections of the combination, and concise, applied coverage of sensor technology is offered. Numerous chapter examples and problems are included, with complete solutions available.

Fundamentals of Sensors for Engineering and Science

2011-04-21

PDF Fundamentals of Sensors for Engineering and Science Download

Author: Patrick F. Dunn
Publisher: CRC Press
ISBN: 1439895252
Category : Technology & Engineering
Languages : en
Pages : 110

Fundamentals of Sensors for Engineering and Science is a practical analysis of sensors and measurement, designed to help readers make informed decisions when selecting an appropriate sensor for a given application. Spurred by a growing demand for information on the evolution of modern sensors, this book evaluates current applications to illustrate

Statistics and Data Analysis for Financial Engineering

2015-04-21

PDF Statistics and Data Analysis for Financial Engineering Download

Author: David Ruppert
Publisher: Springer
ISBN: 1493926144
Category : Business & Economics
Languages : en
Pages : 736

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Optical Scattering

2012

PDF Optical Scattering Download

Author: John C. Stover
Publisher: SPIE-International Society for Optical Engineering
ISBN: 9780819492517
Category : Light
Languages : en
Pages : 0

The first edition of this book concentrated on relating scatter from optically smooth surfaces to the microroughness on those surfaces. After spending six years in the semiconductor industry, Dr. Stover has updated and expanded the third edition. Newly included are scatter models for pits and particles as well as the use of wafer scanners to locate and size isolated surface features. New sections cover the multimillion-dollar wafer scanner business, establishing that microroughness is the noise, not the signal, in these systems. Scatter measurements, now routinely used to determine whether small-surface features are pits or particles and inspiring new technology that provides information on particle material, are also discussed. These new capabilities are now supported by a series of international standards, and a new chapter reviews those documents. New information on scatter from optically rough surfaces has also been added. Once the critical limit is exceeded, scatter cannot be used to determine surface-roughness statistics, but considerable information can still be obtained - especially when measurements are made on mass-produced products. Changes in measurement are covered, and the reader will find examples of scatter measurements made using a camera for a fraction of the cost and in a fraction of the time previously possible. The idea of relating scatter to surface appearance is also discussed, and appearance has its own short chapter. After all, beauty is in the eye of the beholder, and what we see is scattered light.

Loss Models

2012-01-25

PDF Loss Models Download

Author: Stuart A. Klugman
Publisher: John Wiley & Sons
ISBN: 0470391332
Category : Business & Economics
Languages : en
Pages : 758

An update of one of the most trusted books on constructing and analyzing actuarial models Written by three renowned authorities in the actuarial field, Loss Models, Third Edition upholds the reputation for excellence that has made this book required reading for the Society of Actuaries (SOA) and Casualty Actuarial Society (CAS) qualification examinations. This update serves as a complete presentation of statistical methods for measuring risk and building models to measure loss in real-world events. This book maintains an approach to modeling and forecasting that utilizes tools related to risk theory, loss distributions, and survival models. Random variables, basic distributional quantities, the recursive method, and techniques for classifying and creating distributions are also discussed. Both parametric and non-parametric estimation methods are thoroughly covered along with advice for choosing an appropriate model. Features of the Third Edition include: Extended discussion of risk management and risk measures, including Tail-Value-at-Risk (TVaR) New sections on extreme value distributions and their estimation Inclusion of homogeneous, nonhomogeneous, and mixed Poisson processes Expanded coverage of copula models and their estimation Additional treatment of methods for constructing confidence regions when there is more than one parameter The book continues to distinguish itself by providing over 400 exercises that have appeared on previous SOA and CAS examinations. Intriguing examples from the fields of insurance and business are discussed throughout, and all data sets are available on the book's FTP site, along with programs that assist with conducting loss model analysis. Loss Models, Third Edition is an essential resource for students and aspiring actuaries who are preparing to take the SOA and CAS preliminary examinations. It is also a must-have reference for professional actuaries, graduate students in the actuarial field, and anyone who works with loss and risk models in their everyday work. To explore our additional offerings in actuarial exam preparation visit www.wiley.com/go/actuarialexamprep.

Multivariate Statistics

2011-08-15

PDF Multivariate Statistics Download

Author: Yasunori Fujikoshi
Publisher: John Wiley & Sons
ISBN: 0470539860
Category : Mathematics
Languages : en
Pages : 564

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field, the book focuses on high-dimensional and large-scale approximations and details the many basic multivariate methods used to achieve high levels of accuracy. The authors begin with a fundamental presentation of the basic tools and exact distributional results of multivariate statistics, and, in addition, the derivations of most distributional results are provided. Statistical methods for high-dimensional data, such as curve data, spectra, images, and DNA microarrays, are discussed. Bootstrap approximations from a methodological point of view, theoretical accuracies in MANOVA tests, and model selection criteria are also presented. Subsequent chapters feature additional topical coverage including: High-dimensional approximations of various statistics High-dimensional statistical methods Approximations with computable error bound Selection of variables based on model selection approach Statistics with error bounds and their appearance in discriminant analysis, growth curve models, generalized linear models, profile analysis, and multiple comparison Each chapter provides real-world applications and thorough analyses of the real data. In addition, approximation formulas found throughout the book are a useful tool for both practical and theoretical statisticians, and basic results on exact distributions in multivariate analysis are included in a comprehensive, yet accessible, format. Multivariate Statistics is an excellent book for courses on probability theory in statistics at the graduate level. It is also an essential reference for both practical and theoretical statisticians who are interested in multivariate analysis and who would benefit from learning the applications of analytical probabilistic methods in statistics.

Models for Probability and Statistical Inference

2007-12-14

PDF Models for Probability and Statistical Inference Download

Author: James H. Stapleton
Publisher: John Wiley & Sons
ISBN: 0470183403
Category : Mathematics
Languages : en
Pages : 466

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

Periodically Correlated Random Sequences

2007-10-05

PDF Periodically Correlated Random Sequences Download

Author: Harry L. Hurd
Publisher: John Wiley & Sons
ISBN: 047134771X
Category : Mathematics
Languages : en
Pages : 389

Uniquely combining theory, application, and computing, this bookexplores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary)processes has become increasingly popular in a range of researchareas such as meteorology, climate, communications, economics, andmachine diagnostics. Periodically Correlated Random Sequencespresents the main ideas of these processes through the use of basicdefinitions along with motivating, insightful, and illustrativeexamples. Extensive coverage of key concepts is provided, includingsecond-order theory, Hilbert spaces, Fourier theory, and thespectral theory of harmonizable sequences. The authors also providea paradigm for nonparametric time series analysis including testsfor the presence of PC structures. Features of the book include: * An emphasis on the link between the spectral theory of unitaryoperators and the correlation structure of PC sequences * A discussion of the issues relating to nonparametric time seriesanalysis for PC sequences, including estimation of the mean,correlation, and spectrum * A balanced blend of historical background with modernapplication-specific references to periodically correlatedprocesses * An accompanying Web site that features additional exercises aswell as data sets and programs written in MATLAB® forperforming time series analysis on data that may have a PCstructure Periodically Correlated Random Sequences is an ideal text ontime series analysis for graduate-level statistics and engineeringstudents who have previous experience in second-order stochasticprocesses (Hilbert space), vector spaces, random processes, andprobability. This book also serves as a valuable reference forresearch statisticians and practitioners in areas of probabilityand statistics such as time series analysis, stochastic processes,and prediction theory.