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.
Foundations of Bayesian Statistics for Data Scientists: With R and Python
1st Edition
By Alan Agresti, Maria Kateri, Ranjini Grove, Antonietta Mira
June 08, 2026
This book is an overview of the Bayesian approach to applying the most important inferential methods of statistical science. It is designed as a textbook for advanced undergraduate and master’s students in Data Science, Statistics, or Mathematics who are interested in learning about Bayesian ...
Survival Analysis: Principles and Applications in Clinical Trials and Beyond
1st Edition
By Song Yang
April 29, 2026
Survival analysis is crucial in many fields, including biomedical research, actuarial science, reliability analysis, business and customer analytics, econometrics, and social science. It has witnessed significant advancements in recent decades. However, most of this progress remains in scattered ...
Experimental Design for Data Science and Engineering
1st Edition
By V. Roshan Joseph
March 11, 2026
Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from ...
Time Series: A Data Analysis Approach Using R
2nd Edition
By Robert H. Shumway, David S. Stoffer
February 09, 2026
The goals of this new, second edition of this book 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. An expanded feature of this edition is the inclusion of many nontrivial data sets illustrating the...
Bayesian Statistical Methods: With Applications to Machine Learning
2nd Edition
By Brian J. Reich, Sujit K. Ghosh
February 02, 2026
Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple ...
Statistics in Survey Sampling
1st Edition
By Jae Kwang Kim
September 29, 2025
Statistics in Survey Sampling offers a comprehensive and rigorous introduction to the principles and practices of survey sampling. Bridging the gap between statistical theory and real-world data collection, this textbook presents both classical methods and modern developments, equipping readers ...
Exercises and Solutions in Probability and Statistics
1st Edition
By Gary Smith
September 01, 2025
The book contains hundreds of engaging, class-tested statistics exercises (and detailed solutions) that test students’ understanding of the material. Many are educational in their own right—for example, baseball managers who played professional ball were often catchers; stocks that are deleted from...
Applied Nonparametric Statistical Methods
5th Edition
By Nigel Smeeton, Neil H. Spencer, Peter Sprent
March 31, 2025
Nonparametric statistical methods minimize the number of assumptions that need to be made about the distribution of data being analysed, unlike classical parametric methods. As such, they are an essential part of a statistician’s armoury, and this book is an essential resource in their application....
Linear Models with R
3rd Edition
By Julian J. Faraway
March 26, 2025
A Hands-On Way to Learning Data Analysis Part of the core of statistics, linear models are used to make predictions and explain the relationship between the response and the predictors. Understanding linear models is crucial to a broader competence in the practice of statistics. Linear Models with ...
A First Course in Causal Inference
1st Edition
By Peng Ding
July 31, 2024
The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the ...
Analysis of Categorical Data with R
2nd Edition
By Christopher R. Bilder, Thomas M. Loughin
July 31, 2024
Analysis of Categorical Data with R, Second Edition presents a modern account of categorical data analysis using the R software environment. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ...
Beyond Multiple Linear Regression: Applied Generalized Linear Models And Multilevel Models in R
1st Edition
By Paul Roback, Julie Legler
May 27, 2024
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and ...