crc press jan 2021 (4 resultados)

Buch. Condición: Neu. Neuware - Focusing on important aspects of analytics that facilitate innovation, promote entrepreneurship, and improve marketing efficiency and effectiveness, this book provides researchers and business practitioners insight on the techniques, tools, models, and cases of data analytics in the broad areas of innovation, entrepreneurship, and marketing.

Taschenbuch. Condición: Neu. Neuware - The eighth edition of the acclaimed text Operative Pediatric Surgery continues to provide a unique level of comprehensive detail on the full range of surgically treatable conditions presented in neonate and childhood as well as in utero.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Applied Regression and ANOVA Using SAS® has been written specifically for non-statisticians and applied statisticians who are primarily interested in what their data are revealing. Interpretation of results are key throughout this intermediate-level applied statistics book. The authors introduce each method by discussing its characteristic features, reasons for its use, and its underlying assumptions. They then guide readers in applying each method by suggesting a step-by-step approach while providing annotated SAS programs to implement these steps.Those unfamiliar with SAS software will find this book helpful as SAS programming basics are covered in the first chapter. Subsequent chapters give programming details on a need-to-know basis. Experienced as well as entry-level SAS users will find the book useful in applying linear regression and ANOVA methods, as explanations of SAS statements and options chosen for specific methods are provided.Features:-Statistical concepts presented in words without matrix algebra and calculus-Numerous SAS programs, including examples which require minimum programming effort to produce high resolution publication-ready graphics-Practical advice on interpreting results in light of relatively recent views on threshold p-values, multiple testing, simultaneous confidence intervals, confounding adjustment, bootstrapping, and predictor variable selection-Suggestions of alternative approaches when a method's ideal inference conditions are unreasonable for one's dataThis book is invaluable for non-statisticians and applied statisticians who analyze and interpret real-world data. It could be used in a graduate level course for non-statistical disciplines as well as in an applied undergraduate course in statistics or biostatistics. 406 pp. Englisch.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Praise for Bayesian Thinking in Biostatistics:'This thoroughly modern Bayesian book .is a 'must have' as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of illuminating applications. These are activated by excellent coverage of computing methods and provision of code. Their content on model assessment, robustness, data-analytic approaches and predictive assessments.are essential to valid practice. The numerous exercises and professional advice make the book ideal as a text for an intermediate-level course.' -Thomas Louis, Johns Hopkins University'The book introduces all the important topics that one would usually cover in a beginning graduate level class on Bayesian biostatistics. The careful introduction of the Bayesian viewpoint and the mechanics of implementing Bayesian inference in the early chapters makes it a complete self- contained introduction to Bayesian inference for biomedical problems.Another great feature for using this book as a textbook is the inclusion of extensive problem sets, going well beyond construed and simple problems. Many exercises consider real data and studies, providing very useful examples in addition to serving as problems.'- Peter Mueller, University of TexasWith a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently use, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests.Key FeaturesApplies a Bayesian perspective to applications in biomedical scienceHighlights advances in clinical trial designGoes beyond standard statistical models in the book by introducing Bayesian nonparametric methods and illustrating their uses in data analysisEmphasizes estimation of biomedically relevant quantities and assessment of the uncertainty in this estimationProvides programs in the BUGS language, with variants for JAGS and Stan, that one can use or adapt for one's own researchThe intended audience includes graduate students in biostatistics, epidemiology, and biomedical researchers, in generalAuthorsGary L. Rosner is the Eli Kennerly Marshall, Jr., Professor of Oncology at the Johns Hopkins School of Medicine and Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Purushottam (Prakash) W. Laud is Professor in the Division of Biostatistics, and Director of the Biostatistics Shared Resource for the Cancer Center, at the Medical College of Wisconsin. Wesley O. Johnson is professor Emeritus in the Department of Statistics as the University of California, Irvine. 601 pp. Englisch.