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.
An Introduction to Generalized Linear Models
4th Edition
By Annette J. Dobson, Adrian G. Barnett
April 13, 2018
An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection, ...
Statistical Regression and Classification: From Linear Models to Machine Learning
1st Edition
By Norman Matloff
August 01, 2017
This text provides a modern introduction to regression and classification with an emphasis on big data and R. Each chapter is partitioned into a main body section and an extras section. The main body uses math stat very sparingly and always in the context of something concrete, which means that ...
Design of Experiments: An Introduction Based on Linear Models
1st Edition
By Max Morris
May 31, 2017
Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for ...
Generalized Additive Models: An Introduction with R, Second Edition
2nd Edition
By Simon N. Wood
May 30, 2017
The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary ...
Logistic Regression Models
1st Edition
By Joseph M. Hilbe
May 25, 2017
Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The...
Stochastic Processes: From Applications to Theory
1st Edition
By Pierre Del Moral, Spiridon Penev
December 19, 2016
Unlike traditional books presenting stochastic processes in an academic way, this book includes concrete applications that students will find interesting such as gambling, finance, physics, signal processing, statistics, fractals, and biology. Written with an important illustrated guide in the ...
Multivariate Survival Analysis and Competing Risks
1st Edition
By Martin J. Crowder
November 16, 2016
Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions...
Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition
2nd Edition
By Julian J. Faraway
March 24, 2016
Start Analyzing a Wide Range of Problems Since the publication of the bestselling, highly recommended first edition, R has considerably expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric ...
Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data
1st Edition
By Michael Friendly, David Meyer
December 17, 2015
An Applied Treatment of Modern Graphical Methods for Analyzing Categorical Data Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and ...
Mathematical Statistics: Basic Ideas and Selected Topics, Volumes I-II Package
1st Edition
By Peter J. Bickel, Kjell A. Doksum
December 01, 2015
This package includes both Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition, as well as Mathematical Statistics: Basic Ideas and Selected Topics, Volume II. Volume I presents fundamental, classical statistical concepts at the doctorate level without using measure ...
Mathematical Statistics: Basic Ideas and Selected Topics, Volume II
1st Edition
By Peter J. Bickel, Kjell A. Doksum
November 02, 2015
Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors’ previous volume. This second volume focuses on inference in non- and semiparametric models. It not only reexamines the procedures introduced in...
Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition
2nd Edition
By Peter J. Bickel, Kjell A. Doksum
April 13, 2015
Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition presents fundamental, classical statistical concepts at the doctorate level. It covers estimation, prediction, testing, confidence sets, Bayesian analysis, and the general approach of decision theory. This edition ...