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008 150903s2008 xxu| o |||| 0|eng d
020 _a9780387732510
_99780387732510
024 7 _a10.1007/9780387732510
_2doi
035 _avtls000332356
039 9 _a201509030735
_bVLOAD
_c201404122121
_dVLOAD
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040 _aMX-SnUAN
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_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aLongford, Nicholas T.
_eautor
_9302912
245 1 0 _aStudying Human Populations :
_bAn Advanced Course in Statistics /
_cby Nicholas T. Longford.
264 1 _aNew York, NY :
_bSpringer New York,
_c2008.
300 _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 _aANOVA and Ordinary Regression -- Maximum Likelihood Estimation -- Sampling Methods -- The Bayesian Paradigm -- Incomplete Data -- Imperfect Measurement -- Experiments and Observational Studies -- Clinical Trials -- Random Coefficients -- Generalised Linear Models -- Longitudinal and Time-Series Analysis -- Meta-Analysis and Estimating Many Quantities.
520 _aStudying Human Populations is a textbook for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities of sampling, measurement and inference. Statistics is defined broadly as making decisions in the presence of uncertainty that arises as a consequence of limited resources available for collecting information. A connecting link of the presented methods is the perspective of missing information, catering for a diverse class of problems that include nonresponse, imperfect measurement and causal inference. In principle, any problem too complex for our limited analytical toolkit could be converted to a tractable problem if some additional information were available. Ingenuity is called for in declaring such (missing) information constructively, but the universe of problems that we can address is wide open, not limited by a discrete set of procedures. The monograph aims to prepare the reader for the career of an independent social statistician and to serve as a reference for methods, ideas for and ways of studying human populations: formulation of the inferential goals, design of studies, search for the sources of relevant information, analysis and presentation of results. Elementary linear algebra and calculus are prerequisites, although the exposition is quite forgiving, especially in the first few chapters. Familiarity with statistical software at the outset is an advantage, but it can be developed concurrently with studying the text. Nicholas T. Longford directs the statistical research and consulting company SNTL in Reading, England. He had held senior research posts at the Educational Testing Service, Princeton, NJ, and De Montfort University, Leicester, England. He was awarded the first Campion Fellowship by the Royal Statistical Society (2000-2002). He is a member of the editorial boards of the British Journal of Mathematical and Statistical PsychologyB and of Survey Research Methods, and a former Associate Editor of the Journal of Educational and Behavioral Statistics, Journal of Multivariate Analysis and Journals of the Royal Statistical Society Series A and D. He is the author of three other monographs, the latest entitled Missing Data and Small-Area Estimation (Springer, 2005).
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:
_z9780387987354
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-73251-0
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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