For more than a quarter of a century, this internationally recognized series has fostered the growth of statistical science by publishing upper level textbooks of high quality at reasonable prices. These texts, which cover new frontiers as well as developments in core areas, continue to have a major role in shaping the discipline through the education of young scientists both in statistics as well as in fields wherein the role of statistics is becoming increasingly important.
The series covers a very broad domain. Students in upper level undergraduate and graduate courses in biostatistics, epidemiology, probability and statistics will constitute the primary readership for the series. However, others in areas such as engineering, life science, business, environmental science and social science will find books of interest. Scientists in these areas will also find useful references since emphasis is placed on readability, real examples and case studies, and on tying theory into relevant software such as SAS, Stata, and R.
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By Mark Woodward
December 19, 2013
Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of ...
By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin
November 01, 2013
Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data ...
By Peihua Qiu
October 14, 2013
A major tool for quality control and management, statistical process control (SPC) monitors sequential processes, such as production lines and Internet traffic, to ensure that they work stably and satisfactorily. Along with covering traditional methods, Introduction to Statistical Process Control ...
By Olga Korosteleva
August 19, 2013
Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density ...
By Lawrence L. Kupper, Brian. H Neelon, Sean M. O'Brien
June 24, 2013
Exercises and Solutions in Statistical Theory helps students and scientists obtain an in-depth understanding of statistical theory by working on and reviewing solutions to interesting and challenging exercises of practical importance. Unlike similar books, this text incorporates many exercises that...
By Peter Westfall, Kevin S. S. Henning
April 09, 2013
Providing a much-needed bridge between elementary statistics courses and advanced research methods courses, Understanding Advanced Statistical Methods helps students grasp the fundamental assumptions and machinery behind sophisticated statistical topics, such as logistic regression, maximum ...
By David Lunn, Chris Jackson, Nicky Best, Andrew Thomas, David Spiegelhalter
October 02, 2012
Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical ...
By Georg Lindgren
October 01, 2012
Intended for a second course in stationary processes, Stationary Stochastic Processes: Theory and Applications presents the theory behind the field’s widely scattered applications in engineering and science. In addition, it reviews sample function properties and spectral representations for ...
By Hannelore Liero, Silvelyn Zwanzig
July 20, 2011
Based on the authors’ lecture notes, Introduction to the Theory of Statistical Inference presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Suitable for a second-semester undergraduate course on statistical inference, the book ...
By Sean M. O'Brien, Brian. H Neelon, Lawrence Kupper
November 09, 2010
Drawn from nearly four decades of Lawrence L. Kupper’s teaching experiences as a distinguished professor in the Department of Biostatistics at the University of North Carolina, Exercises and Solutions in Biostatistical Theory presents theoretical statistical concepts, numerous exercises, and ...
By Henrik Madsen, Poul Thyregod
November 09, 2010
Bridging the gap between theory and practice for modern statistical model building, Introduction to General and Generalized Linear Models presents likelihood-based techniques for statistical modelling using various types of data. Implementations using R are provided throughout the text, although ...
By Ronald Christensen, Wesley Johnson, Adam Branscum, Timothy E Hanson
July 02, 2010
Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, ...