000			02397 a2200241 4500
001			11411
003			IN-BhIIT
005			20260218164628.0
008			260218b |||||||| |||| 00| 0 eng d
020			_a9780387951638 (hbk.)
040			_aIN-BhIIT
041			_aeng
082			_a530.078 _bROE/P
100			_a Roe, Byron P. _eAuthor _927284
245			_aProbability and statistics in experimental physics / _cByron P. Roe
250			_a2nd ed.
260			_aUSA : _bSpringer, _c2001.
300			_axi, 252 p. : _bill. ; _c22 cm.
504			_aIncludes bibliographical references. and index.
520			_aIntended for advanced undergraduates and graduate students, this book is a practical guide to the use of probability and statistics in experimental physics. The emphasis is on applications and understanding, on theorems and techniques actually used in research. The text is not a comprehensive text in probability and statistics; proofs are sometimes omitted if they do not contribute to intuition in understanding the theorem. The problems, some with worked solutions, introduce the student to the use of computers; occasional reference is made to routines available in the CERN library, but other systems, such as Maple, can also be used. Topics covered include: basic concepts; definitions; some simple results independent of specific distributions; discrete distributions; the normal 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 belts; estimation methods; curve fitting and likelihood ratios; interpolating functions; fitting data with constraints; robust estimation methods. This second edition introduces a new method for dealing with small samples, such as may arise in search experiments, when the data are of low probability. It also includes a new chapter on queuing problems (including a simple, but useful buffer length example). In addition new sections discuss over- and under-coverage using confidence belts, the extended maximum-likelihood method, the use of confidence belts for discrete distributions, estimation of correlation coefficients, and the effective variance method for fitting y = f(x) when both x and y have measurement errors.
650			_aPhysics _927293
942			_cTRB _01
999			_c15323 _d15323