000 03836nam a22003735i 4500
001 280659
003 MX-SnUAN
005 20160429154033.0
007 cr nn 008mamaa
008 150903s2006 xxu| o |||| 0|eng d
020 _a9780817644444
_99780817644444
024 7 _a10.1007/081764444-X
_2doi
035 _avtls000333494
039 9 _a201509030721
_bVLOAD
_c201404120634
_dVLOAD
_c201404090414
_dVLOAD
_y201402041112
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aGood, Phillip I.
_eautor
_9305744
245 1 0 _aResampling Methods :
_bA Practical Guide to Data Analysis /
_cby Phillip I. Good.
250 _aThird Edition.
264 1 _aBoston, MA :
_bBirkhäuser Boston,
_c2006.
300 _axx, 218 páginas 40 ilustraciones
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aSoftware for Resampling -- Estimating Population Parameters -- Comparing Two Populations -- Choosing the Best Procedure -- Experimental Design and Analysis -- Categorical Data -- Multiple Variables and Multiple Hypotheses -- Model Building -- Decision Trees.
520 _a"…the author has packaged an excellent and modern set of topics around the development and use of quantitative models.... If you need to learn about resampling, this book would be a good place to start." —Technometrics (Review of the Second Edition) This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, the book provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. Topics and Features * Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work. * Includes a systematic guide to selecting the correct procedure for a particular application. * Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling. * Suitable for both classroom use and individual self-study. New to the Third Edition * Procedures are grouped by application; a prefatory chapter guides readers to the appropriate reading matter. * Program listings and screen shots now accompany each resampling procedure: Whether one programs in C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-PLUS, Stata, or StatXact, readers will find the program listings and screen shots needed to put each resampling procedure into practice. * To simplify programming, code for readers to download and apply is posted at http://www.springeronline.com/0-8176-4386-9. * Notation has been simplified and, where possible, eliminated. * A glossary and answers to selected exercises are included. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780817643867
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/0-8176-4444-X
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c280659
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