The Resource Statistics and Analysis of Scientific Data, by Massimiliano Bonamente, (electronic resource)
Statistics and Analysis of Scientific Data, by Massimiliano Bonamente, (electronic resource)
 Summary
 The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to twodimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: {u2022} a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. {u2022} a new chapter on the various measures of the mean including logarithmic averages. {u2022} new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. {u2022} a new case study and additional worked examples. {u2022} mathematical derivations and theoretical background material have been appropriately marked,to improve the readability of the text. {u2022} endofchapter summary boxes, for easy reference. As in the first edition, the main pedagogical method is a theorythenapplication approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic
 Language
 eng
 Edition
 2nd ed. 2017.
 Extent
 XVII, 318 p. 40 illus., 4 illus. in color.
 Contents

 Theory of Probability
 Random Variables and Their Distribution
 Sum and Functions of Random Variables
 Estimate of Mean and Variance and Confidence Intervals
 Median, Weighted Mean and Linear Average (NEW)
 Distribution Function of Statistics and Hypothesis Testing
 Maximum Likelihood Fit to a TwoVariable Dataset
 Goodness of Fit and Parameter Uncertainty
 Systematic Errors and Intrinsic Scatter (NEW)
 Fitting Data with Bivariate Errors (NEW)
 Comparison Between Models
 Monte Carlo Methods
 Markov Chains and Monte Carlo Markov Chains
 Statistics for Business Sciences and Addition of Multi{u2013}Variate Analysis (NEW)
 Isbn
 9781493965724
 Label
 Statistics and Analysis of Scientific Data
 Title
 Statistics and Analysis of Scientific Data
 Statement of responsibility
 by Massimiliano Bonamente
 Subject

 Complex Systems
 System theory
 Mathematics
 Statistics
 Statistical Physics and Dynamical Systems
 Statistics for Business/Economics/Mathematical Finance/Insurance
 Appl.Mathematics/Computational Methods of Engineering
 Engineering mathematics
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Physics
 Mathematical Methods in Physics
 Language
 eng
 Summary
 The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to twodimensional data and parameter estimation, Monte Carlo methods and Markov chains. Features new to this edition include: {u2022} a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets. {u2022} a new chapter on the various measures of the mean including logarithmic averages. {u2022} new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors. {u2022} a new case study and additional worked examples. {u2022} mathematical derivations and theoretical background material have been appropriately marked,to improve the readability of the text. {u2022} endofchapter summary boxes, for easy reference. As in the first edition, the main pedagogical method is a theorythenapplication approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic
 Image bit depth
 0
 Literary form
 non fiction
 Series statement
 Graduate Texts in Physics,
 Label
 Statistics and Analysis of Scientific Data, by Massimiliano Bonamente, (electronic resource)
 Related Authorities

 Engineering mathematics
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Statistical Physics and Dynamical Systems
 Appl.Mathematics/Computational Methods of Engineering
 Statistics for Business/Economics/Mathematical Finance/Insurance
 Complex Systems
 Mathematics
 Physics
 System theory
 Mathematical Methods in Physics
 Statistics
 Related Subjects

 Complex Systems
 System theory
 Mathematics
 Statistics
 Statistical Physics and Dynamical Systems
 Statistics for Business/Economics/Mathematical Finance/Insurance
 Appl.Mathematics/Computational Methods of Engineering
 Engineering mathematics
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 Physics
 Mathematical Methods in Physics
 Antecedent source
 mixed
 Carrier category
 online resource
 Carrier category code
 cr
 Carrier MARC source
 rdacarrier
 Color
 not applicable
 Content category
 text
 Content type code
 txt
 Content type MARC source
 rdacontent
 Contents
 Theory of Probability  Random Variables and Their Distribution  Sum and Functions of Random Variables  Estimate of Mean and Variance and Confidence Intervals  Median, Weighted Mean and Linear Average (NEW)  Distribution Function of Statistics and Hypothesis Testing  Maximum Likelihood Fit to a TwoVariable Dataset  Goodness of Fit and Parameter Uncertainty  Systematic Errors and Intrinsic Scatter (NEW)  Fitting Data with Bivariate Errors (NEW)  Comparison Between Models  Monte Carlo Methods  Markov Chains and Monte Carlo Markov Chains  Statistics for Business Sciences and Addition of Multi{u2013}Variate Analysis (NEW)
 http://library.link/vocab/cover_art
 https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781493965724&userID=ebscotest&password=ebscotest
 Dimensions
 unknown
 http://library.link/vocab/discovery_link
 {'f': 'http://opac.lib.rpi.edu/record=b4257685'}
 Edition
 2nd ed. 2017.
 Extent
 XVII, 318 p. 40 illus., 4 illus. in color.
 File format
 multiple file formats
 Form of item
 electronic
 Isbn
 9781493965724
 Level of compression
 uncompressed
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code
 c
 Other physical details
 online resource.
 Quality assurance targets
 absent
 Reformatting quality
 access
 Specific material designation
 remote
Subject
 Appl.Mathematics/Computational Methods of Engineering
 Complex Systems
 Engineering mathematics
 Mathematical Methods in Physics
 Mathematics
 Physics
 Statistical Physics and Dynamical Systems
 Statistics
 Statistics for Business/Economics/Mathematical Finance/Insurance
 Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
 System theory
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.lib.rpi.edu/portal/StatisticsandAnalysisofScientificDataby/dtONvkW67mM/" typeof="WorkExample http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.lib.rpi.edu/portal/StatisticsandAnalysisofScientificDataby/dtONvkW67mM/">Statistics and Analysis of Scientific Data, by Massimiliano Bonamente, (electronic resource)</a></span>  <span property="offers" typeOf="Offer"><span property="offeredBy" typeof="Library ll:Library" resource="http://link.lib.rpi.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.lib.rpi.edu/">Rensselaer Libraries</a></span></span></span></span></div>