Download or read book Data Analysis Techniques for Physical Scientists written by Claude A. Pruneau and published by . This book was released on 2017 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.
Download or read book Data Analysis Techniques for Physical Scientists written by Claude A. Pruneau and published by Cambridge University Press. This book was released on 2017-10-05 with total page 719 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.
Download or read book Data Analysis for Physical Scientists written by Les Kirkup and published by Cambridge University Press. This book was released on 2012-02-16 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing data analysis techniques to help undergraduate students develop the tools necessary for studying and working in the physical sciences.
Download or read book Data Analysis for Physical Scientists written by Les Kirkup and published by . This book was released on 2014-05-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing data analysis techniques to help undergraduate students develop the tools necessary for studying and working in the physical sciences.
Download or read book Data Analysis for Scientists and Engineers written by Edward L. Robinson and published by Princeton University Press. This book was released on 2016-09-20 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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)
Download or read book Data Analysis for Physical Scientists written by Les Kirkup and published by . This book was released on 2012 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The ability to summarise data, compare models and apply computer-based analysis tools are vital skills necessary for studying and working in the physical sciences. This textbook supports undergraduate students as they develop and enhance these skills. Introducing data analysis techniques, this textbook pays particular attention to the internationally recognised guidelines for calculating and expressing measurement uncertainty. This new edition has been revised to incorporate Excel® 2010. It also provides a practical approach to fitting models to data using non-linear least squares, a powerful technique which can be applied to many types of model. Worked examples using actual experimental data help students understand how the calculations apply to real situations. Over 200 in-text exercises and end-of-chapter problems give students the opportunity to use the techniques themselves and gain confidence in applying them. Answers to the exercises and problems are given at the end of the book"--Provided by publisher.
Download or read book Data Reduction and Error Analysis for the Physical Sciences written by Philip R. Bevington and published by McGraw-Hill Science, Engineering & Mathematics. This book was released on 1992 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed as a laboratory companion, student textbook or reference book for professional scientists. The text is for use in one-term numerical analysis, data and error analysis, or computer methods courses, or for laboratory use. It is for the sophomore-junior level, and calculus is a prerequisite. The new edition includes applications for PC use.
Download or read book Data Analysis Methods in Physical Oceanography written by Richard E. Thomson and published by Elsevier. This book was released on 2001-04-03 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis Methods in Physical Oceanography is a practical referenceguide to established and modern data analysis techniques in earth and oceansciences. This second and revised edition is even more comprehensive with numerous updates, and an additional appendix on 'Convolution and Fourier transforms'. Intended for both students and established scientists, the fivemajor chapters of the book cover data acquisition and recording, dataprocessing and presentation, statistical methods and error handling,analysis of spatial data fields, and time series analysis methods. Chapter 5on time series analysis is a book in itself, spanning a wide diversity oftopics from stochastic processes and stationarity, coherence functions,Fourier analysis, tidal harmonic analysis, spectral and cross-spectralanalysis, wavelet and other related methods for processing nonstationarydata series, digital filters, and fractals. The seven appendices includeunit conversions, approximation methods and nondimensional numbers used ingeophysical fluid dynamics, presentations on convolution, statisticalterminology, and distribution functions, and a number of importantstatistical tables. Twenty pages are devoted to references. Featuring:• An in-depth presentation of modern techniques for the analysis of temporal and spatial data sets collected in oceanography, geophysics, and other disciplines in earth and ocean sciences.• A detailed overview of oceanographic instrumentation and sensors - old and new - used to collect oceanographic data.• 7 appendices especially applicable to earth and ocean sciences ranging from conversion of units, through statistical tables, to terminology and non-dimensional parameters. In praise of the first edition: "(...)This is a very practical guide to the various statistical analysis methods used for obtaining information from geophysical data, with particular reference to oceanography(...)The book provides both a text for advanced students of the geophysical sciences and a useful reference volume for researchers." Aslib Book Guide Vol 63, No. 9, 1998 "(...)This is an excellent book that I recommend highly and will definitely use for my own research and teaching." EOS Transactions, D.A. Jay, 1999 "(...)In summary, this book is the most comprehensive and practical source of information on data analysis methods available to the physical oceanographer. The reader gets the benefit of extremely broad coverage and an excellent set of examples drawn from geographical observations." Oceanography, Vol. 12, No. 3, A. Plueddemann, 1999 "(...)Data Analysis Methods in Physical Oceanography is highly recommended for a wide range of readers, from the relative novice to the experienced researcher. It would be appropriate for academic and special libraries." E-Streams, Vol. 2, No. 8, P. Mofjelf, August 1999
Download or read book Statistical Data Analysis written by Glen Cowan and published by Oxford University Press. This book was released on 1998 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
Download or read book Data Analysis with Excel written by Les Kirkup and published by Cambridge University Press. This book was released on 2002-03-07 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential introduction to data analysis techniques using spreadsheets, for undergraduate and graduate students.
Download or read book Statistics for Physical Sciences written by Brian Martin and published by Academic Press. This book was released on 2012-01-19 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Statistics in physical science is principally concerned with the analysis of numerical data, so in Chapter 1 there is a review of what is meant by an experiment, and how the data that it produces are displayed and characterized by a few simple numbers"--
Download or read book Statistical Data Analysis for the Physical Sciences written by Adrian Bevan and published by Cambridge University Press. This book was released on 2013-05-09 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data analysis lies at the heart of every experimental science. Providing a modern introduction to statistics, this book is ideal for undergraduates in physics. It introduces the necessary tools required to analyse data from experiments across a range of areas, making it a valuable resource for students. In addition to covering the basic topics, the book also takes in advanced and modern subjects, such as neural networks, decision trees, fitting techniques and issues concerning limit or interval setting. Worked examples and case studies illustrate the techniques presented, and end-of-chapter exercises help test the reader's understanding of the material.
Download or read book Statistical Techniques for Data Analysis written by John K. Taylor and published by CRC Press. This book was released on 2004-01-14 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze stat
Download or read book Data Analysis Techniques for High Energy Physics Experiments written by R. K. Bock and published by Cambridge University Press. This book was released on 2009-06-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: High-energy physics - the science of the fundamental particles nature - has become one of the most complex and demanding disciplines of natural science. The observation of particle interactions involves the analysis of large and intricate data samples. The very high cost of these experiments makes the full and correct use of the information imperative. Successful interpretation of the data requires the application of advanced mathematical algorithms and computer techniques in all stages of the analysis. The necessary and available techniques of all steps of the analysis have been assembled in a single book. All four authors have had many years' involvement with high-energy physics experiments at CERN, DESY and other particle accelerators around the world. They have written this book both as an introduction and to inform the reader on the most advanced techniques of data analysis in this field. It will be of great value to people involved in experimental research in particle physics, including beginning graduates, computer electronic engineers and senior academics.
Download or read book Data Analysis for the Life Sciences with R written by Rafael A. Irizarry and published by CRC Press. This book was released on 2016-10-04 with total page 461 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research. The authors proceed from relatively basic concepts related to computed p-values to advanced topics related to analyzing highthroughput data. They include the R code that performs this analysis and connect the lines of code to the statistical and mathematical concepts explained.
Download or read book Data Analysis Techniques for Nuclear and Particle Physicists written by Claude Pruneau and published by CRC Press. This book was released on 2016-05-15 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an advanced data analysis textbook for scientists specializing in the areas of particle physics, nuclear physics, and related subfields. As a practical guide for robust, comprehensive data analysis, it focuses on realistic techniques to explain instrumental effects. The topics are relevant for engineers, scientists, and astroscientists working in the fields of geophysics, chemistry, and the physical sciences. The book serves as a reference for more senior scientists while being eminently accessible to advanced undergraduate and graduate students.
Download or read book Quantitative Methods of Data Analysis for the Physical Sciences and Engineering written by Douglas G. Martinson and published by Cambridge University Press. This book was released on 2018-04-30 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides thorough and comprehensive coverage of most of the new and important quantitative methods of data analysis for graduate students and practitioners. In recent years, data analysis methods have exploded alongside advanced computing power, and it is critical to understand such methods to get the most out of data, and to extract signal from noise. The book excels in explaining difficult concepts through simple explanations and detailed explanatory illustrations. Most unique is the focus on confidence limits for power spectra and their proper interpretation, something rare or completely missing in other books. Likewise, there is a thorough discussion of how to assess uncertainty via use of Expectancy, and the easy to apply and understand Bootstrap method. The book is written so that descriptions of each method are as self-contained as possible. Many examples are presented to clarify interpretations, as are user tips in highlighted boxes.
