000 03436nam a22004935i 4500
001 978-1-4614-7984-0
003 DE-He213
005 20140220082831.0
007 cr nn 008mamaa
008 130807s2013 xxu| s |||| 0|eng d
020 _a9781461479840
_9978-1-4614-7984-0
024 7 _a10.1007/978-1-4614-7984-0
_2doi
050 4 _aQC174.7-175.36
072 7 _aPHS
_2bicssc
072 7 _aPHDT
_2bicssc
072 7 _aSCI055000
_2bisacsh
082 0 4 _a621
_223
100 1 _aBonamente, Massimiliano.
_eauthor.
245 1 0 _aStatistics and Analysis of Scientific Data
_h[electronic resource] /
_cby Massimiliano Bonamente.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXV, 301 p. 39 illus., 2 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aGraduate Texts in Physics,
_x1868-4513
505 0 _aTheory of Probability -- Random Variables and Their Distribution -- Sum and Functions of Random Variables -- Estimate of Mean and Variance and Confidence Intervals -- Distribution Function of Statistics and Hypothesis Testing -- Maximum Likelihood Fit to a Two-Variable Dataset -- Goodness of Fit and Parameter Uncertainty -- Comparison Between Models -- Monte Carlo Methods -- Markov Chains and Monte Carlo Markov Chains -- A: Numerical Tables -- B: Solutions.
520 _aStatistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and analytical methods that are essential for the present-day analyst of scientific data. Topics covered include probability theory, distribution functions of statistics, fits to two-dimensional datasheets and parameter estimation, Monte Carlo methods and Markov chains. Equal attention is paid to the theory and its practical application, and results from classic experiments in various fields are used to illustrate the importance of statistics in the analysis of scientific data. The main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and proactive use of the material for practical applications. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the students' understanding of the topic.
650 0 _aPhysics.
650 0 _aDistribution (Probability theory).
650 0 _aMathematical statistics.
650 1 4 _aPhysics.
650 2 4 _aStatistical Physics, Dynamical Systems and Complexity.
650 2 4 _aProbability Theory and Stochastic Processes.
650 2 4 _aStatistical Theory and Methods.
650 2 4 _aNumerical and Computational Physics.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461479833
830 0 _aGraduate Texts in Physics,
_x1868-4513
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-7984-0
912 _aZDB-2-PHA
999 _c96015
_d96015