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Probability and Statistics for Physical Sciences
- 2nd Edition - September 5, 2023
- Authors: Brian Martin, Mark Hurwitz
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 8 9 6 9 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 8 9 7 0 - 8
Probability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical scienc… Read more
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Request a sales quoteProbability and Statistics for Physical Sciences, Second Edition is an accessible guide to commonly used concepts and methods in statistical analysis used in the physical sciences. This brief yet systematic introduction explains the origin of key techniques, providing mathematical background and useful formulas. The text does not assume any background in statistics and is appropriate for a wide-variety of readers, from first-year undergraduate students to working scientists across many disciplines.
- Provides a collection of useful formulas with mathematical background
- Includes worked examples throughout and end-of-chapter problems for practice
- Offers a logical progression through topics and methods in statistics and probability
Students in undergraduate and graduate courses introducing or utilizing basic statistics (ie, Intro Stats for non-Math/Stats majors), especially in physical science programs (physics, chemistry, astronomy, earth science, etc)Professionals, researchers, academics across Physical Sciences applying statistics in their work, who require a refresher to the subject
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- Acknowledgments
- CHAPTER 1. Statistics, experiments, and data
- 1.1 Experiments and observations
- 1.2 Random variables and sampling
- 1.3 Displaying data
- 1.4 Summarizing data numerically
- 1.5 Large samples
- 1.6 Experimental errors
- Problems 1
- CHAPTER 2. Probability
- 2.1. Sample spaces and events
- 2.2. Axioms and calculus of probability
- 2.3. Conditional and marginal probabilities
- 2.4. Permutations and combinations
- 2.5. The meaning of probability
- Problems 2
- CHAPTER 3. Probability distributions I: Basic concepts
- 3.1. Random variables
- 3.2. Single variable
- 3.3. Several variables
- 3.4. Functions of a random variable
- Problems 3
- CHAPTER 4. Probability distributions II: Examples
- 4.1 Continuous variables
- 4.2 Discrete variables
- Problems 4
- CHAPTER 5. Sampling and estimation
- 5.1. Random samples and estimators
- 5.2. Estimators for the mean, variance, and covariance
- 5.3. Laws of large numbers and the central limit theorem
- 5.4. Experimental errors
- 5.5. Monte Carlo method and simulations
- Problems 5
- CHAPTER 6. Sampling distributions associated with the normal distribution
- 6.1. Chi-squared distribution
- 6.2. Student’s t distribution
- 6.3. F distribution
- 6.4. Relations between χ2, t, and F distributions
- Problems 6
- Chapter 7. Parameter estimation I: Maximum likelihood and minimum variance
- 7.1. Estimation of a single parameter
- 7.2. Variance of an estimator
- 7.3. Simultaneous estimation of several parameters
- 7.4. Minimum variance
- Problems 7
- CHAPTER 8. Parameter estimation II: Least-squares and other methods
- 8.1. Unconstrained linear least-squares
- 8.2. Linear least-squares with constraints
- 8.3. Nonlinear least-squares
- 8.4. Other methods
- Problems 8
- CHAPTER 9. Interval estimation
- 9.1 Confidence intervals: Basic ideas
- 9.2 Confidence intervals: General method
- 9.3 Normal distribution
- 9.4 Poisson distribution
- 9.5 Large samples
- 9.6 Confidence intervals near boundaries
- 9.7 Bayesian confidence intervals
- Problems 9
- CHAPTER 10. Hypothesis testing I: Parameters
- 10.1. Statistical hypotheses
- 10.2. General hypotheses: Likelihood ratios
- 10.3. Normal distribution
- 10.4. Other distributions
- 10.5. Analysis of variance
- 10.6. Bayesian hypothesis testing
- Problems 10
- CHAPTER 11. Hypothesis testing II: Other tests
- 11.1 Goodness-of-fit tests
- 11.2 Tests for independence
- 11.3 Nonparametric tests
- Problems 11
- Appendix A. Miscellaneous mathematics
- Appendix B. Optimization of nonlinear functions
- Appendix C. Statistical tables
- Appendix D. Answers to selected problems
- Bibliography
- Index
- No. of pages: 416
- Language: English
- Edition: 2
- Published: September 5, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780443189692
- eBook ISBN: 9780443189708
BM
Brian Martin
Prof. Brian R. Martin graduated from Birmingham University with a BSc in Physics and then moved to University College London (1962-1965) to take a PhD in Theoretical Physics. He was a Ford Foundation Fellow at the Institute for Theoretical Physics, Copenhagen University, Copenhagen; a NATO Postdoctoral Fellowship at the Neils Bohr Institute, Copenhagen; and a Research Associate in the Physics Department of Brookhaven National Laboratory, New York. Returning to University College London, he served as a Lecturer, then a Reader and Professor, before becoming Head of Department (1993-2004). Professor Martin retired as Professor Emeritus in October 2005.
Affiliations and expertise
Professor Emeritus, University College London, UKMH
Mark Hurwitz
Dr. Mark F. Hurwitz graduated from Northwestern University with a BS in Mechanical Engineering and then worked as an engineer at Xerox Corporation while earning an MS in Mechanical and Aerospace Engineering at the University of Rochester. He earned a PhD at Cornell University in Theoretical and Applied Mechanics during an extensive R&D career in the filtration and separations industry at Pall Corporation, where he was inventor of 12 US patents with multiple foreign cognates. Returning to Cornell University, he was an Adjunct Professor in the Robert Frederick Smith School of Chemical and Biomolecular Engineering, before moving to administration and becoming the Chief Research Compliance Officer.
Affiliations and expertise
Chief Research Compliance Officer and Research Integrity Officer, Cornell University, NY, USARead Probability and Statistics for Physical Sciences on ScienceDirect