000 04429nam a22005295i 4500
001 978-0-387-73251-0
003 DE-He213
005 20250710084017.0
007 cr nn 008mamaa
008 100301s2008 xxu| s |||| 0|eng d
020 _a9780387732510
_a99780387732510
024 7 _a10.1007/978-0-387-73251-0
_2doi
082 0 4 _a519.5
_223
100 1 _aLongford, Nicholas T.
_eauthor.
245 1 0 _aStudying Human Populations
_h[recurso electrónico] :
_bAn Advanced Course in Statistics /
_cby Nicholas T. Longford.
264 1 _aNew York, NY :
_bSpringer New York,
_c2008.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Texts in Statistics,
_x1431-875X
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).
650 0 _aSTATISTICS.
650 0 _aEPIDEMIOLOGY.
650 0 _aELECTRONIC DATA PROCESSING.
650 0 _aCOMPUTER SIMULATION.
650 0 _aBIOMETRICS.
650 0 _aMATHEMATICAL STATISTICS.
650 0 _aPSYCHOMETRICS.
650 1 4 _aSTATISTICS.
650 2 4 _aSTATISTICAL THEORY AND METHODS.
650 2 4 _aEPIDEMIOLOGY.
650 2 4 _aPSYCHOMETRICS.
650 2 4 _aBIOMETRICS.
650 2 4 _aSIMULATION AND MODELING.
650 2 4 _aNUMERIC COMPUTING.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387987354
830 0 _aSpringer Texts in Statistics,
_x1431-875X
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-73251-0
_zVer el texto completo en las instalaciones del CICY
912 _aZDB-2-SMA
942 _2ddc
_cER
999 _c58454
_d58454