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Probability and statistics in the ph...

Roe, Byron P.

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Probability and statistics in the physical sciences

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probability and statistics in the physical sciences/ by Byron P. Roe.
Author:	Roe, Byron P.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xiii, 285 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1. Basic Probability Concepts -- Chapter 2. Some Initial Definitions -- Chapter 3. Some Results Independent of Specific Distributions -- Chapter 4. Discrete Distributions and Combinatorials -- Chapter 5. Specific Discrete Distributions -- Chapter 6. The Normal (or Gaussian) Distribution and Other Continuous Distributions -- Chapter 7. Generating Functions and Characteristic Functions -- Chapter 8. The Monte Carlo Method: Computer Simulation of Experiments -- Chapter 9. Queueing Theory and Other Probability Questions -- Chapter 10. Two-Dimensional and Multidimensional Distributions -- Chapter 11. The Central Limit Theorem -- Chapter 12. Choosing Hypotheses and Estimating Parameters from Experimental Data -- Chapter 13. Methods of Least Squares (Regression Analysis) -- Chapter 14. Inverse Probability; Confidence Limits -- Chapter 15. Curve Fitting -- Chapter 16. Fitting Data with Correlations and Constraints -- Chapter 17. Bartlett S Function; Estimating Likelihood Ratios Needed for an Experiment -- Chapter 18. Interpolating Functions and Unfolding Problems -- Chapter 19. Beyond Maximum Likelihood and Least Squares; Robust Methods -- Chapter 20. Characterization of Events -- Appendix -- Index.
Contained By:	Springer Nature eBook
Subject:	Statistical physics. -
Online resource:	https://doi.org/10.1007/978-3-030-53694-7
ISBN:	9783030536947

Probability and statistics in the physical sciences
Roe, Byron P.

Probability and statistics in the physical sciences[electronic resource] /by Byron P. Roe. - Third edition. - Cham :Springer International Publishing :2020. - xiii, 285 p. :ill., digital ;24 cm. - Undergraduate texts in physics,2510-411X. - Undergraduate texts in physics..

Chapter 1. Basic Probability Concepts -- Chapter 2. Some Initial Definitions -- Chapter 3. Some Results Independent of Specific Distributions -- Chapter 4. Discrete Distributions and Combinatorials -- Chapter 5. Specific Discrete Distributions -- Chapter 6. The Normal (or Gaussian) Distribution and Other Continuous Distributions -- Chapter 7. Generating Functions and Characteristic Functions -- Chapter 8. The Monte Carlo Method: Computer Simulation of Experiments -- Chapter 9. Queueing Theory and Other Probability Questions -- Chapter 10. Two-Dimensional and Multidimensional Distributions -- Chapter 11. The Central Limit Theorem -- Chapter 12. Choosing Hypotheses and Estimating Parameters from Experimental Data -- Chapter 13. Methods of Least Squares (Regression Analysis) -- Chapter 14. Inverse Probability; Confidence Limits -- Chapter 15. Curve Fitting -- Chapter 16. Fitting Data with Correlations and Constraints -- Chapter 17. Bartlett S Function; Estimating Likelihood Ratios Needed for an Experiment -- Chapter 18. Interpolating Functions and Unfolding Problems -- Chapter 19. Beyond Maximum Likelihood and Least Squares; Robust Methods -- Chapter 20. Characterization of Events -- Appendix -- Index.

This book, now in its third edition, offers a practical guide to the use of probability and statistics in experimental physics that is of value for both advanced undergraduates and graduate students. Focusing on applications and theorems and techniques actually used in experimental research, it includes worked problems with solutions, as well as homework exercises to aid understanding. Suitable for readers with no prior knowledge of statistical techniques, the book comprehensively discusses the topic and features a number of interesting and amusing applications that are often neglected. Providing an introduction to neural net techniques that encompasses deep learning, adversarial neural networks, and boosted decision trees, this new edition includes updated chapters with, for example, additions relating to generating and characteristic functions, Bayes' theorem, the Feldman-Cousins method, Lagrange multipliers for constraints, estimation of likelihood ratios, and unfolding problems.

ISBN: 9783030536947

Standard No.: 10.1007/978-3-030-53694-7doiSubjects--Topical Terms:

536281
Statistical physics.

LC Class. No.: QC174.8

Dewey Class. No.: 530.1595

Probability and statistics in the physical sciences
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100 1 $a Roe, Byron P. $3 3504486
245 1 0 $a Probability and statistics in the physical sciences $h [electronic resource] / $c by Byron P. Roe.
250 $a Third edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xiii, 285 p. : $b ill., digital ; $c 24 cm.
490 1 $a Undergraduate texts in physics, $x 2510-411X
505 0 $a Chapter 1. Basic Probability Concepts -- Chapter 2. Some Initial Definitions -- Chapter 3. Some Results Independent of Specific Distributions -- Chapter 4. Discrete Distributions and Combinatorials -- Chapter 5. Specific Discrete Distributions -- Chapter 6. The Normal (or Gaussian) Distribution and Other Continuous Distributions -- Chapter 7. Generating Functions and Characteristic Functions -- Chapter 8. The Monte Carlo Method: Computer Simulation of Experiments -- Chapter 9. Queueing Theory and Other Probability Questions -- Chapter 10. Two-Dimensional and Multidimensional Distributions -- Chapter 11. The Central Limit Theorem -- Chapter 12. Choosing Hypotheses and Estimating Parameters from Experimental Data -- Chapter 13. Methods of Least Squares (Regression Analysis) -- Chapter 14. Inverse Probability; Confidence Limits -- Chapter 15. Curve Fitting -- Chapter 16. Fitting Data with Correlations and Constraints -- Chapter 17. Bartlett S Function; Estimating Likelihood Ratios Needed for an Experiment -- Chapter 18. Interpolating Functions and Unfolding Problems -- Chapter 19. Beyond Maximum Likelihood and Least Squares; Robust Methods -- Chapter 20. Characterization of Events -- Appendix -- Index.
520 $a This book, now in its third edition, offers a practical guide to the use of probability and statistics in experimental physics that is of value for both advanced undergraduates and graduate students. Focusing on applications and theorems and techniques actually used in experimental research, it includes worked problems with solutions, as well as homework exercises to aid understanding. Suitable for readers with no prior knowledge of statistical techniques, the book comprehensively discusses the topic and features a number of interesting and amusing applications that are often neglected. Providing an introduction to neural net techniques that encompasses deep learning, adversarial neural networks, and boosted decision trees, this new edition includes updated chapters with, for example, additions relating to generating and characteristic functions, Bayes' theorem, the Feldman-Cousins method, Lagrange multipliers for constraints, estimation of likelihood ratios, and unfolding problems.
650 0 $a Statistical physics. $3 536281
650 0 $a Probabilities. $3 518889
650 0 $a Mathematical physics. $3 516853
650 1 4 $a Mathematical Methods in Physics. $3 890898
650 2 4 $a Particle and Nuclear Physics. $3 1067136
650 2 4 $a Astronomy, Astrophysics and Cosmology. $3 890823
650 2 4 $a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. $3 1005896
650 2 4 $a Data-driven Science, Modeling and Theory Building. $3 2210495
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Undergraduate texts in physics. $3 3447739
856 4 0 $u https://doi.org/10.1007/978-3-030-53694-7
950 $a Physics and Astronomy (SpringerNature-11651)