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008 150903s2005 xxk| o |||| 0|eng d
020 _a9781846281686
_99781846281686
024 7 _a10.1007/1846281687
_2doi
035 _avtls000343705
039 9 _a201509030749
_bVLOAD
_c201404120951
_dVLOAD
_c201404090728
_dVLOAD
_y201402061202
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aDekking, Frederik Michel.
_eautor
_9323199
245 1 2 _aA Modern Introduction to Probability and Statistics :
_bUnderstanding Why and How /
_cby Frederik Michel Dekking, Cornelis Kraaikamp, Hendrik Paul Lopuhaä, Ludolf Erwin Meester.
264 1 _aLondon :
_bSpringer London,
_c2005.
300 _axv, 486 páginas 120 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aSpringer Texts in Statistics,
_x1431-875X
500 _aSpringer eBooks
505 0 _aWhy probability and statistics? -- Outcomes, events, and probability -- Conditional probability and independence -- Discrete random variables -- Continuous random variables -- Simulation -- Expectation and variance -- Computations with random variables -- Joint distributions and independence -- Covariance and correlation -- More computations with more random variables -- The Poisson process -- The law of large numbers -- The central limit theorem -- Exploratory data analysis: graphical summaries -- Exploratory data analysis: numerical summaries -- Basic statistical models -- The bootstrap -- Unbiased estimators -- Efficiency and mean squared error -- Maximum likelihood -- The method of least squares -- Confidence intervals for the mean -- More on confidence intervals -- Testing hypotheses: essentials -- Testing hypotheses: elaboration -- The t-test -- Comparing two samples.
520 _aProbability and Statistics are studied by most science students, usually as a second- or third-year course. Many current texts in the area are just cookbooks and, as a result, students do not know why they perform the methods they are taught, or why the methods work. The strength of this book is that it readdresses these shortcomings; by using examples, often from real-life and using real data, the authors can show how the fundamentals of probabilistic and statistical theories arise intuitively. It provides a tried and tested, self-contained course, that can also be used for self-study. A Modern Introduction to Probability and Statistics has numerous quick exercises to give direct feedback to the students. In addition the book contains over 350 exercises, half of which have answers, of which half have full solutions. A website at www.springeronline.com/1-85233-896-2 gives access to the data files used in the text, and, for instructors, the remaining solutions. The only pre-requisite for the book is a first course in calculus; the text covers standard statistics and probability material, and develops beyond traditional parametric models to the Poisson process, and on to useful modern methods such as the bootstrap. This will be a key text for undergraduates in Computer Science, Physics, Mathematics, Chemistry, Biology and Business Studies who are studying a mathematical statistics course, and also for more intensive engineering statistics courses for undergraduates in all engineering subjects.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aKraaikamp, Cornelis.
_eautor
_9323200
700 1 _aLopuhaä, Hendrik Paul.
_eautor
_9323201
700 1 _aMeester, Ludolf Erwin.
_eautor
_9323202
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781852338961
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/1-84628-168-7
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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