1. Probability and Statistical Inference
Robert Bartoszynski (Author), Magdalena Niewiadomska-Bugaj (Author)
Publisher: Wiley-Interscience; 2 edition (January 2, 2008)
Language: English
ISBN-10: 0471696935
ISBN-13: 978-0471696933
Probability and Statistical Inference, Second Edition introduces key probability and statis-tical concepts through non-trivial, real-world examples and promotes the developmentof intuition rather than simple application. With its coverage of the recent advancements in computer-intensive methods, this update successfully provides the comp-rehensive tools needed to develop a broad understanding of the theory of statisticsand its probabilistic foundations. This outstanding new edition continues to encouragereaders to recognize and fully understand the why, not just the how, behind the concepts,theorems, and methods of statistics. Clear explanations are presented and appliedto various examples that help to impart a deeper understanding of theorems and methods—from fundamental statistical concepts to computational details. Additional features of this Second Edition include:

• A new chapter on random samples
• Coverage of computer-intensive techniques in statistical inference featuring Monte Carlo and resampling methods, such as bootstrap and permutation tests, bootstrap confidence intervals with supporting R codes, and additional examples available via the book's FTP site
• Treatment of survival and hazard function, methods of obtaining estimators, and Bayes estimating
• Real-world examples that illuminate presented concepts
• Exercises at the end of each section
  

Providing a straightforward, contemporary approach to modern-day statistical applications, Probability and Statistical Inference, Second Edition is an ideal text for advanced undergraduate- and graduate-level courses in probability and statistical inference. It also serves as a valuable reference for practitioners in any discipline who wish to gain further insight into the latest statistical tools.





2. Nonparametric Statistics with Applications to Science and Engineering
Paul H. Kvam  (Author), Brani Vidakovic (Author)
Publisher: Wiley-Interscience; 1 edition (July 23, 2007) Language: English ISBN-10: 0470081473 ISBN-13: 978-0470081471 A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.



這本是免費,抱歉未加上書籤
3. Biostatistics: A Foundation for Analysis in the Health Sciences

Publisher: Wiley; 9 edition (December 31, 2008) Language: English ISBN-10: 0470105828 ISBN-13: 978-0470105825
Allied health professionals rely on Biostatistics for its high standards of statistical accuracy. It helps them develop a set of statistical tools that are relevant to their field. Now in its ninth edition, the book integrates new applications from several biological science fields throughout the pages. Each chapter now opens with bulleted objectives that highlight the main ideas. Summary boxes of formulae and statistical rules are presented for easy reference and review. Support is also provided for multiple programs such as SPSS, SAS, and STATA, in addition to Minitab. This includes screen captures and technology boxes with step-by-step help. Health professionals will then gain the ability to use technology to analyze data.





4. Statistical Rules of Thumb
Gerald van Belle (Author)  
Publisher: Wiley-Interscience; 2nd edition (September 2, 2008) Language: English ISBN-10: 0470144483 ISBN-13: 978-0470144480
Sensibly organized for quick reference, Statistical Rules of Thumb, Second Edition compiles simple rules that are widely applicable, robust, and elegant, and each captures key statistical concepts. This unique guide to the use of statistics for designing, conducting, and analyzing research studies illustrates real-world statistical applications through examples from fields such as public health and environmental studies. Along with an insightful discussion of the reasoning behind every technique, this easy-to-use handbook also conveys the various possibilities statisticians must think of when designing and conducting a study or analyzing its data. Each chapter presents clearly defined rules related to inference, covariation, experimental design, consultation, and data representation, and each rule is organized and discussed under five succinct headings: introduction; statement and illustration of the rule; the derivation of the rule; a concluding discussion; and exploration of the concept's extensions. The author also introduces new rules of thumb for topics such as sample size for ratio analysis, absolute and relative risk, ANCOVA cautions, and dichotomization of continuous variables. Additional features of the Second Edition include:

• Additional rules on Bayesian topics
• New chapters on observational studies and Evidence-Based Medicine (EBM)
• Additional emphasis on variation and causation
• Updated material with new references, examples, and sources
  

A related Web site provides a rich learning environment and contains additional rules, presentations by the author, and a message board where readers can share their own strategies and discoveries. Statistical Rules of Thumb, Second Edition is an ideal supplementary book for courses in experimental design and survey research methods at the upper-undergraduate and graduate levels. It also serves as an indispensable reference for statisticians, researchers, consultants, and scientists who would like to develop an understanding of the statistical foundations of their research efforts.A related website www.vanbelle.org provides additional rules, author presentations and more  




5. Cluster Analysis
Brian S. Everitt (Author), Sabine Landau (Author), Morven Leese (Author), Daniel Stahl (Author)  
Publisher: Wiley; 5 edition (March 8, 2011) Language: English ISBN-10: 0470749911 ISBN-13: 978-0470749913
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics. This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.
Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis. Key Features: • Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis.
• Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies
• Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data. Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.