Skip to main content
  • Textbook
  • © 2020

Probability and Statistics in the Physical Sciences

Authors:

  • Features worked problems with solutions plus homework exercises
  • Includes amusing, often-neglected applications
  • Assumes no prior knowledge of statistical techniques
  • Offers an introduction to neural net techniques
  • Request lecturer material: sn.pub/lecturer-material

Part of the book series: Undergraduate Texts in Physics (UNTEPH)

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (20 chapters)

  1. Front Matter

    Pages i-xiii
  2. Basic Probability Concepts

    • Byron P. Roe
    Pages 1-4
  3. Some Initial Definitions

    • Byron P. Roe
    Pages 5-13
  4. Specific Discrete Distributions

    • Byron P. Roe
    Pages 33-41
  5. The Central Limit Theorem

    • Byron P. Roe
    Pages 107-117
  6. Inverse Probability; Confidence Limits

    • Byron P. Roe
    Pages 145-172
  7. Curve Fitting

    • Byron P. Roe
    Pages 173-199

About this book

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.

Reviews

“The depth and the manner in which the material is treated will make it easy for the students to transition to more advanced topics such as deep learning, machine learning and artificial intelligence after perusing the book. … Roe’s book is a wonderful, forward looking introduction to probability and statistics and its applications. Hence, I have no hesitations whatsoever in recommending the book – both to the students and instructors.” (Mogadalai P Gururajan, Contemporary Physics, August 19, 2021)

Authors and Affiliations

  • Randall Laboratory, University of Michigan, Ann Arbor, USA

    Byron P. Roe

About the author

Byron P. Roe is Professor Emeritus of Physics at the University of Michigan. He is a specialist in Experimental Nuclear and Subatomic Physics and Experimental Elementary Particle Physics. Professor Roe worked on an extensive number of experiments at Fermilab, CERN, and Argonne for more than 50 years and was often the spokesperson or co-spokesperson for these experiments. He has worked with the MiniBooNE neutrino experiment for almost 20 years. He is a Fellow of the American Physical Society.

Bibliographic Information

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access