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.
Probability and Bayesian Modeling
1st Edition
By Jim Albert, Jingchen Hu
December 18, 2019
Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus background. The first part of the book provides a broad view of probability including foundations, conditional probability, discrete and continuous distributions, and...
Time Series: A Data Analysis Approach Using R
1st Edition
By Robert H. Shumway, David S. Stoffer
May 21, 2019
The goals of this text are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data. A useful feature of the presentation is the inclusion of nontrivial data sets illustrating the richness of potential ...
The Analysis of Time Series: An Introduction with R
7th Edition
By Chris Chatfield, Haipeng Xing
May 09, 2019
This new edition of this classic title, now in its seventh edition, presents a balanced and comprehensive introduction to the theory, implementation, and practice of time series analysis. The book covers a wide range of topics, including ARIMA models, forecasting methods, spectral analysis, linear ...
Theory of Spatial Statistics: A Concise Introduction
1st Edition
By M.N.M. van Lieshout
March 11, 2019
Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, ...
Introduction to Probability, Second Edition
2nd Edition
By Joseph K. Blitzstein, Jessica Hwang
February 08, 2019
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google ...
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...