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Probability, statistics and simulati...

Rotondi, Alberto.

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Probability, statistics and simulation = with application programs written in R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probability, statistics and simulation/ by Alberto Rotondi, Paolo Pedroni, Antonio Pievatolo.
Reminder of title:	with application programs written in R /
Author:	Rotondi, Alberto.
other author:	Pedroni, Paolo.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xv, 639 p. :ill., digital ;24 cm.
[NT 15003449]:	1 Probability -- 2 Representation of random phenomena -- 3 Basic probability theory -- 4 Multivariate Probability Theory -- 5 Functions of random variables -- 6 Basic statistics: parameter estimation -- 7 Basic statistics: hypothesis testing -- 8 Monte Carlo methods -- 9 Applications of Monte Carlo methods -- 10 Statistical inference and likelihood -- 11 Least squares -- 12 Experimental data analysis -- Appendix A: Table of symbols 533 -- Appendix B: R software 535 -- Appendix C: Moment-generating functions 539 -- Appendix D: Solutions of problems 543 -- Appendix E: Tables.
Contained By:	Springer Nature eBook
Subject:	Mathematical statistics. -
Online resource:	https://doi.org/10.1007/978-3-031-09429-3
ISBN:	9783031094293

Probability, statistics and simulation = with application programs written in R /
Rotondi, Alberto.

Probability, statistics and simulationwith application programs written in R /[electronic resource] :by Alberto Rotondi, Paolo Pedroni, Antonio Pievatolo. - Cham :Springer International Publishing :2022. - xv, 639 p. :ill., digital ;24 cm. - UNITEXT. La matematica per il 3+2,v. 1392038-5757 ;. - UNITEXT.La matematica per il 3+2 ;v. 139..

1 Probability -- 2 Representation of random phenomena -- 3 Basic probability theory -- 4 Multivariate Probability Theory -- 5 Functions of random variables -- 6 Basic statistics: parameter estimation -- 7 Basic statistics: hypothesis testing -- 8 Monte Carlo methods -- 9 Applications of Monte Carlo methods -- 10 Statistical inference and likelihood -- 11 Least squares -- 12 Experimental data analysis -- Appendix A: Table of symbols 533 -- Appendix B: R software 535 -- Appendix C: Moment-generating functions 539 -- Appendix D: Solutions of problems 543 -- Appendix E: Tables.

This book presents in a compact form the program carried out in introductory statistics courses and discusses some essential topics for research activity, such as Monte Carlo simulation techniques, methods of statistical inference, best fit and analysis of laboratory data. All themes are developed starting from fundamentals, highlighting their applicative aspects, up to the detailed description of several cases particularly relevant for technical and scientific research. The text is dedicated to university students in scientific fields and to all researchers who have to solve practical problems by applying data analysis and simulation procedures. The R software is adopted throughout the book, with a rich library of original programs accessible to the readers through a website.

ISBN: 9783031094293

Standard No.: 10.1007/978-3-031-09429-3doiSubjects--Topical Terms:

516858
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Probability, statistics and simulation = with application programs written in R /
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505 0 $a 1 Probability -- 2 Representation of random phenomena -- 3 Basic probability theory -- 4 Multivariate Probability Theory -- 5 Functions of random variables -- 6 Basic statistics: parameter estimation -- 7 Basic statistics: hypothesis testing -- 8 Monte Carlo methods -- 9 Applications of Monte Carlo methods -- 10 Statistical inference and likelihood -- 11 Least squares -- 12 Experimental data analysis -- Appendix A: Table of symbols 533 -- Appendix B: R software 535 -- Appendix C: Moment-generating functions 539 -- Appendix D: Solutions of problems 543 -- Appendix E: Tables.
520 $a This book presents in a compact form the program carried out in introductory statistics courses and discusses some essential topics for research activity, such as Monte Carlo simulation techniques, methods of statistical inference, best fit and analysis of laboratory data. All themes are developed starting from fundamentals, highlighting their applicative aspects, up to the detailed description of several cases particularly relevant for technical and scientific research. The text is dedicated to university students in scientific fields and to all researchers who have to solve practical problems by applying data analysis and simulation procedures. The R software is adopted throughout the book, with a rich library of original programs accessible to the readers through a website.
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