A Practical Guide to Data Analysis for Physical Science Students

Author: Louis Lyons,Lyons Louis

Publisher: Cambridge University Press

ISBN: 9780521424639

Category: Science

Page: 95

View: 1671

This textbook is intended for undergraduates who are carrying out laboratory experiments in the physical sciences for the first time. It is a practical guide on how to analyze data and estimate errors. The necessary formulas for performing calculations are given, and the ideas behind them are explained, although this is not a formal text on statistics. Specific examples are worked through step by step in the text. Emphasis is placed on the need to think about whether a calculated error is sensible. Students should take this book with them to the laboratory, and the format is intended to make this convenient. The book will provide the necessary understanding of what is involved, should inspire confidence in the method of estimating errors, and enable numerical calculations without too much effort.
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Einführung in Statistik und Messwertanalyse für Physiker

Monographie

Author: G. Bohm,G. Zech

Publisher: N.A

ISBN: 9783540257592

Category:

Page: 400

View: 1990

Die Einf]hrung in die Statistik und Messwertanalyse f]r Physiker richtet sich weniger an mathematischen \berlegungen aus, sondern stellt die praktische Anwendung in den Vordergrund und schdrft die Intuition experimentelle Ergebnisse richtig einzuschdtzen. Zahlreiche ausf]hrlich betrachtete Beispiele dienen dazu, hdufig bei der Datenanalyse gemachte Fehler zu vermeiden (unsinnige Anwendung des Chi-Quadrattests, Funktionenanpassung bei falscher Parametrisierung, Entfaltung mit willk]rlicher Regularisierung). Ein besonderes Augenmerk wird auf den Vergleich von Daten mit Monte-Carlo-Simulationen gelenkt. Moderne Experimente kommen nicht ohne Simulation aus. Deshalb ist es wichtig zu wissen, wie Parameteranpassungen und Entfaltungen in diesem Fall durchgef]rt werden. Au_erdem werden den Studierenden moderne Entwicklungen der Statistik nahegebracht, die in dlteren Lehrb]chern nicht behandelt werden.
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Resampling Methods

A Practical Guide to Data Analysis

Author: Phillip I. Good

Publisher: Springer Science & Business Media

ISBN: 081764444X

Category: Mathematics

Page: 218

View: 2006

This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
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Practical Statistics for Astronomers

Author: J. V. Wall,C. R. Jenkins

Publisher: Cambridge University Press

ISBN: 1107393701

Category: Science

Page: N.A

View: 1996

Astronomy needs statistical methods to interpret data, but statistics is a many-faceted subject that is difficult for non-specialists to access. This handbook helps astronomers analyze the complex data and models of modern astronomy. This second edition has been revised to feature many more examples using Monte Carlo simulations, and now also includes Bayesian inference, Bayes factors and Markov chain Monte Carlo integration. Chapters cover basic probability, correlation analysis, hypothesis testing, Bayesian modelling, time series analysis, luminosity functions and clustering. Exercises at the end of each chapter guide readers through the techniques and tests necessary for most observational investigations. The data tables, solutions to problems, and other resources are available online at www.cambridge.org/9780521732499. Bringing together the most relevant statistical and probabilistic techniques for use in observational astronomy, this handbook is a practical manual for advanced undergraduate and graduate students and professional astronomers.
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Practical Data Analysis in Chemistry

Author: Marcel Maeder,Yorck-Michael Neuhold

Publisher: Elsevier

ISBN: 9780080548838

Category: Science

Page: 340

View: 2642

The majority of modern instruments are computerised and provide incredible amounts of data. Methods that take advantage of the flood of data are now available; importantly they do not emulate 'graph paper analyses' on the computer. Modern computational methods are able to give us insights into data, but analysis or data fitting in chemistry requires the quantitative understanding of chemical processes. The results of this analysis allows the modelling and prediction of processes under new conditions, therefore saving on extensive experimentation. Practical Data Analysis in Chemistry exemplifies every aspect of theory applicable to data analysis using a short program in a Matlab or Excel spreadsheet, enabling the reader to study the programs, play with them and observe what happens. Suitable data are generated for each example in short routines, this ensuring a clear understanding of the data structure. Chapter 2 includes a brief introduction to matrix algebra and its implementation in Matlab and Excel while Chapter 3 covers the theory required for the modelling of chemical processes. This is followed by an introduction to linear and non-linear least-squares fitting, each demonstrated with typical applications. Finally Chapter 5 comprises a collection of several methods for model-free data analyses. * Includes a solid introduction to the simulation of equilibrium processes and the simulation of complex kinetic processes. * Provides examples of routines that are easily adapted to the processes investigated by the reader * 'Model-based' analysis (linear and non-linear regression) and 'model-free' analysis are covered
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A Student's Guide to Data and Error Analysis

Author: Herman J. C. Berendsen

Publisher: Cambridge University Press

ISBN: 1139497855

Category: Technology & Engineering

Page: N.A

View: 9115

All students taking laboratory courses within the physical sciences and engineering will benefit from this book, whilst researchers will find it an invaluable reference. This concise, practical guide brings the reader up-to-speed on the proper handling and presentation of scientific data and its inaccuracies. It covers all the vital topics with practical guidelines, computer programs (in Python), and recipes for handling experimental errors and reporting experimental data. In addition to the essentials, it also provides further background material for advanced readers who want to understand how the methods work. Plenty of examples, exercises and solutions are provided to aid and test understanding, whilst useful data, tables and formulas are compiled in a handy section for easy reference.
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Statistical Data Analysis

Author: Glen Cowan

Publisher: Oxford University Press

ISBN: 0198501560

Category: Mathematics

Page: 197

View: 322

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 taken from 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).
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Data Analysis Methods in Physical Oceanography

Author: William J. Emery,Richard E. Thomson

Publisher: Gulf Professional Publishing

ISBN: 9780444507570

Category: Science

Page: 638

View: 3700

Data Analysis Methods in Physical Oceanography is a practical reference guide to established and modern data analysis techniques in earth and ocean sciences. 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 five major chapters of the book cover data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. Chapter 5 on time series analysis is a book in itself, spanning a wide diversity of topics from stochastic processes and stationarity, coherence functions, Fourier analysis, tidal harmonic analysis, spectral and cross-spectral analysis, wavelet and other related methods for processing nonstationary data series, digital filters, and fractals. The seven appendices include unit conversions, approximation methods and nondimensional numbers used in geophysical fluid dynamics, presentations on convolution, statistical terminology, and distribution functions, and a number of important statistical 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
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Statistik-Workshop für Programmierer

Author: Allen Downey

Publisher: O'Reilly Germany

ISBN: 3868993428

Category:

Page: 138

View: 9755

Wenn Sie programmieren konnen, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einfuhrung in die Statistik zeigt Ihnen, wie Sie rechnergestutzt, anstatt auf mathematischem Weg Datenanalysen mit Python durchfuhren konnen. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch fuhrt Sie anhand eines durchgangigen Fallbeispiels durch eine vollstandige Datenanalyse -- von der Datensammlung uber die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmoglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie uber das Schreiben und Testen von Code ein Verstandnis fur die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Uberprufen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zuganglich sind. Lernen Sie etwas uber Themen, die in Einfuhrungen ublicherweise nicht vermittelt werden, beispielsweise uber die Bayessche Schatzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.
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Essenzielle Quantenmechanik

für Elektrotechniker und Informatiker

Author: Peter Deák

Publisher: John Wiley & Sons

ISBN: 3527683852

Category: Science

Page: 228

View: 9061

Der Autor zeigt an Beispielen aus der Festkörperelektronik und der Quanteninformationstechnologie, welche Rolle quantenmechanische Konzepte in der modernen Energie-, Kommunikations- und Informationstechnik spielen.
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Visualize This!

Author: Nathan Yau

Publisher: John Wiley & Sons

ISBN: 3527760229

Category: Statistics / Graphic methods / Data processing

Page: 422

View: 1216

A guide on how to visualise and tell stories with data, providing practical design tips complemented with step-by-step tutorials.
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Excel 2016 for Physical Sciences Statistics

A Guide to Solving Practical Problems

Author: Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton

Publisher: Springer

ISBN: 3319400754

Category: Mathematics

Page: 246

View: 3056

This book shows the capabilities of Microsoft Excel in teaching physical science statistics effectively. Similar to the previously published Excel 2013 for Physical Sciences Statistics, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in physical science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Physical Sciences Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand physical science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.
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Data Analysis

A Bayesian Tutorial

Author: Devinderjit Sivia,John Skilling

Publisher: OUP Oxford

ISBN: 0198568320

Category: Mathematics

Page: 264

View: 1243

Focusing on Bayesian methods and maximum entropy, this book shows how a few fundamental rules can be used to tackle a variety of problems in data analysis. Topics covered include reliability analysis, multivariate optimisation, least-squares and maximum likelihood, and more.
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Statistics, Data Mining, and Machine Learning in Astronomy

A Practical Python Guide for the Analysis of Survey Data

Author: Željko Ivezić,Andrew J. Connolly,Jacob T VanderPlas,Alexander Gray

Publisher: Princeton University Press

ISBN: 1400848911

Category: Science

Page: 552

View: 622

As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers
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Excel 2013 for Physical Sciences Statistics

A Guide to Solving Practical Problems

Author: Thomas J. Quirk,Meghan H. Quirk,Howard F. Horton

Publisher: Springer

ISBN: 3319289640

Category: Mathematics

Page: 242

View: 3223

This book shows the is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical science problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2013 for Physical Sciences Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work. Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand science problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.
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Compendium of Practical Astronomy: Instrumentation and reduction techniques

Author: Harry J. Augensen,Wulff D. Heintz

Publisher: N.A

ISBN: 9783540535966

Category: Science

Page: 540

View: 4419

The Compendium of Practical Astronomy is a revised and enlarged English version of the fourth edition of G. Roth's famous handbook for stargazers. In three volumes 28 carefully edited articles, aimed especially at amateur astronomers and students and teachers of astronomy in high schools and colleges, cover the length and breadth of practical astronomy. Volume 1 contains information on modern instrumentation and reduction techniques, including spherical astronomy, error estimations, telescope mountings, astrophotography, and more. Volume 2 covers the planetary system, with contributions on artificial satellites, comets, the polar aurorae, and the effects of the atmosphere on observational data. Volume 3 is devoted to stellar objects, variable stars and binary stars in particular. An introduction to the astronomical literature and a comprehensive chapter on astronomy education and instructional aids make the Compendium a useful complement to any college library, in addition to its being essential reading for all practical astronomers.
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Reporting Results

A Practical Guide for Engineers and Scientists

Author: David C. van Aken,William F. Hosford

Publisher: Cambridge University Press

ISBN: 1107394376

Category: Technology & Engineering

Page: N.A

View: 4153

This brief guide is ideal for science and engineering students and professionals to help them communicate technical information clearly, accurately, and effectively. The focus is on the most common communication forms, including laboratory reports, research articles, and oral presentations, and on common issues that arise in classroom and professional practice. This book will be especially useful to students in a first chemistry or physics laboratory course. Advanced courses will often use the same formatting as required for submission to technical journals or for technical report writing, which is the focus of this book. Good communication habits are appropriate in all forms of technical communication. This book will help the reader develop effective communication skills. It is also ideal as a reference on stylistic and grammar issues throughout a technical career. Unlike most texts, which concentrate on writing style, this book also treats oral presentations, graphing, and analysis of data.
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