Introduction To Statistics And Data Analysis For Physicists

Introduction to statistics and data analysis for physicists PDF
Author: Gerhard Bohm
Publisher:
ISBN: 9783935702416
Size: 53.39 MB
Format: PDF, Mobi
Category :
Languages : en
Pages : 447
View: 5675

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Book Description:

Statistical Data Analysis For The Physical Sciences

Statistical Data Analysis for the Physical Sciences PDF
Author: Adrian Bevan
Publisher: Cambridge University Press
ISBN: 1107067596
Size: 57.22 MB
Format: PDF, ePub, Docs
Category : Science
Languages : en
Pages :
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Book Description: 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.

Statistical Methods For Data Analysis In Particle Physics

Statistical Methods for Data Analysis in Particle Physics PDF
Author: Luca Lista
Publisher: Springer
ISBN: 331920176X
Size: 13.47 MB
Format: PDF
Category : Science
Languages : en
Pages : 172
View: 1723

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Book Description: This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.

Data Analysis For Scientists And Engineers

Data Analysis for Scientists and Engineers PDF
Author: Edward L. Robinson
Publisher: Princeton University Press
ISBN: 0691169926
Size: 57.46 MB
Format: PDF, ePub
Category : Science
Languages : en
Pages : 408
View: 7730

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Book Description: 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

Data Analysis PDF
Author: Siegmund Brandt
Publisher: Springer Science & Business Media
ISBN: 3319037625
Size: 37.41 MB
Format: PDF, Mobi
Category : Science
Languages : en
Pages : 523
View: 5653

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Book Description: 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.

An Introduction To Data Analysis In R

An Introduction to Data Analysis in R PDF
Author: Alfonso Zamora Saiz
Publisher: Springer Nature
ISBN: 3030489973
Size: 69.44 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 276
View: 2079

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Book Description: This textbook offers an easy-to-follow, practical guide to modern data analysis using the programming language R. The chapters cover topics such as the fundamentals of programming in R, data collection and preprocessing, including web scraping, data visualization, and statistical methods, including multivariate analysis, and feature exercises at the end of each section. The text requires only basic statistics skills, as it strikes a balance between statistical and mathematical understanding and implementation in R, with a special emphasis on reproducible examples and real-world applications. This textbook is primarily intended for undergraduate students of mathematics, statistics, physics, economics, finance and business who are pursuing a career in data analytics. It will be equally valuable for master students of data science and industry professionals who want to conduct data analyses.

Statistik Workshop F R Programmierer

Statistik Workshop f  r Programmierer PDF
Author: Allen B. Downey
Publisher: O'Reilly Germany
ISBN: 3868993436
Size: 53.82 MB
Format: PDF, Kindle
Category : Computers
Languages : de
Pages : 160
View: 374

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Book Description: Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen 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 zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.

Statistische Und Numerische Methoden Der Datenanalyse

Statistische und numerische Methoden der Datenanalyse PDF
Author: Volker Blobel
Publisher: Springer-Verlag
ISBN: 3663056902
Size: 80.23 MB
Format: PDF, ePub
Category : Technology & Engineering
Languages : de
Pages : 358
View: 2699

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Book Description: Der Umfang des Datenmaterials in Wissenschaft und Technik nimmt immer schneller zu; seine Auswertung und Beurteilung erweisen sich zunehmend als die eigentliche Schwierigkeit bei vielen wichtigen Problemen. Dem steht zwar ein bisher ungebrochenes Anwachsen von Rechnerleistung und die zunehmende Verfügbarkeit mächtiger Algorithmen gegenüber, aber es ist oft nicht einfach, von diesen Hilfsmitteln den richtigen und professionellen Gebrauch zu machen. Dieses Buch, entstanden aus der Praxis der Verarbeitung großer Datenmengen, will eine Einführung und Hilfe auf diesem Gebiet geben.

Data Analysis For Physical Scientists

Data Analysis for Physical Scientists PDF
Author: Les Kirkup
Publisher: Cambridge University Press
ISBN: 0521883725
Size: 52.21 MB
Format: PDF, ePub, Docs
Category : Mathematics
Languages : en
Pages : 510
View: 6357

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Book Description: Introducing data analysis techniques to help undergraduate students develop the tools necessary for studying and working in the physical sciences.

Statistical Methods For Physical Science

Statistical Methods for Physical Science PDF
Author:
Publisher: Academic Press
ISBN: 9780080860169
Size: 37.84 MB
Format: PDF, ePub
Category : Science
Languages : en
Pages : 542
View: 5677

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Book Description: This volume of Methods of Experimental Physics provides an extensive introduction to probability and statistics in many areas of the physical sciences, with an emphasis on the emerging area of spatial statistics. The scope of topics covered is wide-ranging-the text discusses a variety of the most commonly used classical methods and addresses newer methods that are applicable or potentially important. The chapter authors motivate readers with their insightful discussions. Examines basic probability, including coverage of standard distributions, time series models, and Monte Carlo methods Describes statistical methods, including basic inference, goodness of fit, maximum likelihood, and least squares Addresses time series analysis, including filtering and spectral analysis Includes simulations of physical experiments Features applications of statistics to atmospheric physics and radio astronomy Covers the increasingly important area of modern statistical computing