Basic Concepts Of Data And Error Analysis
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Basic Concepts Of Data And Error Analysis
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Author : Panayiotis Nicos Kaloyerou
language : en
Publisher:
Release Date : 2018
Basic Concepts Of Data And Error Analysis written by Panayiotis Nicos Kaloyerou and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Engineering mathematics categories.
This introductory textbook explains the concepts and methods of data and error analysis needed for laboratory experiment write-ups, especially physics and engineering experiments. The book contains the material needed for beginning students, e.g., first year university students, college students (enrolled on a certificate or diploma course) and even A-level students. Nevertheless, it also covers the required material for higher year university laboratories, including the final year. Only essential concepts and methods needed for the day-to-day performance of experiments and their subsequent analysis and presentation are included and, at the same time, presented as simply as possible. Non-essential detail is avoided. Chapter five is a stand-alone introduction to probability and statistics aimed at providing a theoretical background to the data and error analysis chapters one to four. Computer methods are introduced in Chapter six. The author hopes this book will serve as a constant reference.
Introduction To Error Analysis
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Author : Jack Merrin
language : de
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-08-29
Introduction To Error Analysis written by Jack Merrin and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-29 with categories.
Great scientists master the math behind the science. Do you still delay mastering data analysis, keeping you from more accurate, rigorous, and higher certainty conclusions? Jack Merrin, Ph.D. Princeton University, is a physicist who has helped hundreds of students with math and physics, taught physics labs, and used error analysis through 25 years of research. You can surely learn the right statistical methods from Jack. Introduction to Error Analysis is more than a collection of ad-hoc statistical theory. It is an easy-to-read blueprint used by scientists for presenting correct results. Transform your experimental perspective to confidence. Learn reusable principles for each new scientific project. This book covers reporting measurements and uncertainties, propagation of error, combining results, curve fitting, essential statistical concepts, and much, much, more. You might love this book if: You are doing lab reports or actual research, and it's time to get serious about data analysis. You want to focus on the essential calculations, not on time-wasting theory. You want adaptable MATLAB code for each different calculation. Hey, no need to reinvent the wheel. You want to reach correct and unique results using the established convention. You want to know what is correct to spot bad scientific literature. Introduction to Error Analysis is the concise book you need to start building your successful scientific career. If you like easy-to-follow lessons, practical examples, insightful tips, and an author who actually cares about you getting it right, then you'll love Jack's book. Buy Introduction to Error Analysis to start refining your data analysis skills today!
Basic Concepts Of Data And Error Analysis
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Author : Panayiotis Nicos Kaloyerou
language : en
Publisher: Springer
Release Date : 2018-10-24
Basic Concepts Of Data And Error Analysis written by Panayiotis Nicos Kaloyerou and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-24 with Technology & Engineering categories.
This introductory textbook explains the concepts and methods of data and error analysis needed for laboratory experiment write-ups, especially physics and engineering experiments. The book contains the material needed for beginning students, e.g., first year university students, college students (enrolled on a certificate or diploma course) and even A-level students. Nevertheless, it also covers the required material for higher year university laboratories, including the final year. Only essential concepts and methods needed for the day-to-day performance of experiments and their subsequent analysis and presentation are included and, at the same time, presented as simply as possible. Non-essential detail is avoided. Chapter five is a stand-alone introduction to probability and statistics aimed at providing a theoretical background to the data and error analysis chapters one to four. Computer methods are introduced in Chapter six. The author hopes this book will serve as a constant reference.
Data Reduction And Error Analysis For The Physical Sciences
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Author : Philip R. Bevington
language : en
Publisher: McGraw-Hill Companies
Release Date : 1969
Data Reduction And Error Analysis For The Physical Sciences written by Philip R. Bevington and has been published by McGraw-Hill Companies this book supported file pdf, txt, epub, kindle and other format this book has been release on 1969 with Mathematics categories.
The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation is developed from a practical point of view, including enough derivation to justify the results, but emphasizing methods of handling data more than theory. The text provides a variety of numerical and graphical techniques. Computer programs that support these techniques will be available on an accompanying website in both Fortran and C++.
Data Reduction And Error Analysis For The Physical Sciences
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Author : Philip Bevington
language : en
Publisher:
Release Date : 2003
Data Reduction And Error Analysis For The Physical Sciences written by Philip Bevington and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Science categories.
The purpose of this book is to provide an introduction to the concepts of statistical analysis of data for students at the undergraduate and graduate level, and to provide tools for data reduction and error analysis commonly required in the physical sciences. The presentation is developed from a practical point of view, including enough derivation to justify the results, but emphasizing methods of handling data more than theory. The text provides a variety of numerical and graphical techniques. Computer programs that support these techniques will be available on an accompanying website in both Fortran and C++.
Measurements And Their Uncertainties
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Author : Ifan Hughes
language : en
Publisher: Oxford University Press
Release Date : 2010-07
Measurements And Their Uncertainties written by Ifan Hughes and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07 with Mathematics categories.
This short guide to modern error analysis is primarily intended to be used in undergraduate laboratories in the physical sciences. No prior knowledge of statistics is assumed. The necessary concepts are introduced where needed and illustrated graphically. The book emphasises the use of computers for error calculations and data fitting.
A Student S Guide To Data And Error Analysis
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Author : Herman J. C. Berendsen
language : en
Publisher:
Release Date : 2011
A Student S Guide To Data And Error Analysis written by Herman J. C. Berendsen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Electronic book categories.
"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"--
Core Concepts In Data Analysis Summarization Correlation And Visualization
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Author : Boris Mirkin
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-05
Core Concepts In Data Analysis Summarization Correlation And Visualization written by Boris Mirkin 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 2011-04-05 with Computers categories.
Core Concepts in Data Analysis: Summarization, Correlation and Visualization provides in-depth descriptions of those data analysis approaches that either summarize data (principal component analysis and clustering, including hierarchical and network clustering) or correlate different aspects of data (decision trees, linear rules, neuron networks, and Bayes rule). Boris Mirkin takes an unconventional approach and introduces the concept of multivariate data summarization as a counterpart to conventional machine learning prediction schemes, utilizing techniques from statistics, data analysis, data mining, machine learning, computational intelligence, and information retrieval. Innovations following from his in-depth analysis of the models underlying summarization techniques are introduced, and applied to challenging issues such as the number of clusters, mixed scale data standardization, interpretation of the solutions, as well as relations between seemingly unrelated concepts: goodness-of-fit functions for classification trees and data standardization, spectral clustering and additive clustering, correlation and visualization of contingency data. The mathematical detail is encapsulated in the so-called “formulation” parts, whereas most material is delivered through “presentation” parts that explain the methods by applying them to small real-world data sets; concise “computation” parts inform of the algorithmic and coding issues. Four layers of active learning and self-study exercises are provided: worked examples, case studies, projects and questions.
Comet For Data Science
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Author : Angelica Lo Duca
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-08-26
Comet For Data Science written by Angelica Lo Duca and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Computers categories.
Gain the key knowledge and skills required to manage data science projects using Comet Key Features • Discover techniques to build, monitor, and optimize your data science projects • Move from prototyping to production using Comet and DevOps tools • Get to grips with the Comet experimentation platform Book Description This book provides concepts and practical use cases which can be used to quickly build, monitor, and optimize data science projects. Using Comet, you will learn how to manage almost every step of the data science process from data collection through to creating, deploying, and monitoring a machine learning model. The book starts by explaining the features of Comet, along with exploratory data analysis and model evaluation in Comet. You'll see how Comet gives you the freedom to choose from a selection of programming languages, depending on which is best suited to your needs. Next, you will focus on workspaces, projects, experiments, and models. You will also learn how to build a narrative from your data, using the features provided by Comet. Later, you will review the basic concepts behind DevOps and how to extend the GitLab DevOps platform with Comet, further enhancing your ability to deploy your data science projects. Finally, you will cover various use cases of Comet in machine learning, NLP, deep learning, and time series analysis, gaining hands-on experience with some of the most interesting and valuable data science techniques available. By the end of this book, you will be able to confidently build data science pipelines according to bespoke specifications and manage them through Comet. What you will learn • Prepare for your project with the right data • Understand the purposes of different machine learning algorithms • Get up and running with Comet to manage and monitor your pipelines • Understand how Comet works and how to get the most out of it • See how you can use Comet for machine learning • Discover how to integrate Comet with GitLab • Work with Comet for NLP, deep learning, and time series analysis Who this book is for This book is for anyone who has programming experience, and wants to learn how to manage and optimize a complete data science lifecycle using Comet and other DevOps platforms. Although an understanding of basic data science concepts and programming concepts is needed, no prior knowledge of Comet and DevOps is required.
An Introduction To Error Analysis
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Author : John Robert Taylor
language : en
Publisher: Univ Science Books
Release Date : 1997-01-01
An Introduction To Error Analysis written by John Robert Taylor and has been published by Univ Science Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-01-01 with Mathematics categories.
Problems after each chapter