Chapman & Hall/CRC Texts in Statistical Science
About the Book Series
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.
Please contact us if you have an idea for a book for the series.
Introduction to the Theory of Statistical Inference
1st Edition
By Hannelore Liero, Silvelyn Zwanzig
August 12, 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 ...
Exercises and Solutions in Biostatistical Theory
1st Edition
By Lawrence Kupper, Brian. H Neelon, Sean M. O'Brien
November 19, 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 ...
Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians
1st Edition
By Ronald Christensen, Wesley Johnson, Adam Branscum, Timothy E Hanson
July 07, 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, ...
Design and Analysis of Experiments with SAS
1st Edition
By John Lawson
May 11, 2010
A culmination of the author’s many years of consulting and teaching, Design and Analysis of Experiments with SAS provides practical guidance on the computer analysis of experimental data. It connects the objectives of research to the type of experimental design required, describes the actual ...
Statistics in Human Genetics and Molecular Biology
1st Edition
By Cavan Reilly
June 24, 2009
Focusing on the roles of different segments of DNA, Statistics in Human Genetics and Molecular Biology provides a basic understanding of problems arising in the analysis of genetics and genomics. It presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses ...
Applied Stochastic Modelling
2nd Edition
By Byron J.T. Morgan
November 28, 2008
Highlighting modern computational methods, Applied Stochastic Modelling, Second Edition provides students with the practical experience of scientific computing in applied statistics through a range of interesting real-world applications. It also successfully revises standard probability and ...
Bayesian Methods for Data Analysis
3rd Edition
By Bradley P. Carlin, Thomas A. Louis
July 26, 2008
Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian ...
A Primer on Linear Models
1st Edition
By John F. Monahan
April 21, 2008
A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample ...
Time Series Analysis
1st Edition
By Henrik Madsen
December 11, 2007
With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the ...
Introduction to Statistical Methods for Clinical Trials
1st Edition
Edited
By Thomas D. Cook, David L. DeMets
November 19, 2007
Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical ...
Introduction to Randomized Controlled Clinical Trials
2nd Edition
By John N.S. Matthews
June 26, 2006
Evidence from randomized controlled clinical trials is widely accepted as the only sound basis for assessing the efficacy of new medical treatments. Statistical methods play a key role in all stages of these trials, including their justification, design, and analysis. This second edition of ...
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition
2nd Edition
By Dani Gamerman, Hedibert F. Lopes
May 10, 2006
While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new ...