000 | 03436nam a22004935i 4500 | ||
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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 |
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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 |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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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 |