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-Physics, Topology, Logic and Computation: A Rosetta Stone- by John C. Baez adn Mike Stay
-Quantum Physics for Scientists and Technologists- by Paul Sanghera (Repost)
Physics Democracy and Public Space: The Physical Sites of Democratic Performance
Statistical and Thermal Physics - With Computer Applications
Introduction to the Physics of the Earth's Interior (Cambridge Topics in Mineral Ph) by Jean Paul Poirier (Repost)
Physics Principles and Labs for Physical Fitness, 7 edition by Wener W.K. Hoeger
Paul W. Zitzewitz, T. G. Elliott, "Physics: Principles and Problems" (Repost)
Physics Research for a Future in Space: The Role of Life and Physical Sciences
"Physics, Topology, Logic and Computation: A Rosetta Stone" by John C. Baez adn Mike Stay
Physics Black Hat - Physical Device Security. Exploiting Hardware and Software
Physics Lifetime Physical Fitness and Wellness - A Personalized Program, 10th edition
The Dreams That Stuff Is Made Of - The Most Astounding Papers of Quantum Physics--and How They Shook the Scientific World
"Quantum Physics for Scientists and Technologists" by Paul Sanghera (Repost)
C-algebras and applications to physics by A. Dold
Hyberbolic Conservation Laws in Continuum Physics (Grundlehren der mathematischen Wissenschaften) by C. M. Dafermos
Applications of Random Matrices in Physics by Edouard Brezin
Handbook of Chemistry and Physics (repost)
Few-Body Problems in Physics [Repost]
Physics Maya Training Tutorials - Maya Physical Dynamics CD-ViH
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Probability and Statistics in Experimental Physics
Posted on 2010-04-12
|  |
More Byron P. Roe ¡°" This book is a practical introduction to the use of for graduate students and advanced undergraduates. It is intended as a practical guide, not as a comprehensive text in probability and statistics. The emphasis is on applications and understanding, on theorems and techniques that are actually used in experimental physics. Proofs of theorems are generally omitted unless they contribute to the intuition in understanding and applying the theorem. The problems, some with worked solutions, introduce the student to the use of computers; occasional reference is made to some of the Fortran routines available in the CERN library, but other systems, such as Maple, will also be useful. Topics covered include: basic concepts and definitions; general results, independent of specific distributions; discrete distributions; the normal distribution and other continuous distributions; generating and characteristic functions; the Monte Carlo method and computer simulations; multi-dimensional distributions; the central limit theorem; inverse probability and confidence limits; estimation methods; curve fitting, robustness estimates, and likelihood ratios; interpolating functions and unfolding problems; fitting data with constraints; robust estimation methods. "
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