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.
Modelling Survival Data in Medical Research
4th Edition
By David Collett
May 31, 2023
Modelling Survival Data in Medical Research, Fourth Edition, describes the analysis of survival data, illustrated using a wide range of examples from biomedical research. Written in a non-technical style, it concentrates on how the techniques are used in practice. Starting with standard methods for...
Fundamentals of Mathematical Statistics
1st Edition
By Steffen Lauritzen
April 17, 2023
Fundamentals of Mathematical Statistics is meant for a standard one-semester advanced undergraduate or graduate-level course in Mathematical Statistics. It covers all the key topics—statistical models, linear normal models, exponential families, estimation, asymptotics of maximum likelihood, ...
Applied Categorical and Count Data Analysis
2nd Edition
By Wan Tang, Hua He, Xin M. Tu
April 06, 2023
Developed from the authors’ graduate-level biostatistics course, Applied Categorical and Count Data Analysis, Second Edition explains how to perform the statistical analysis of discrete data, including categorical and count outcomes. The authors have been teaching categorical data analysis courses ...
Statistical Theory: A Concise Introduction
2nd Edition
By Felix Abramovich, Ya'acov Ritov
December 23, 2022
Designed for a one-semester advanced undergraduate or graduate statistical theory course, Statistical Theory: A Concise Introduction, Second Edition clearly explains the underlying ideas, mathematics, and principles of major statistical concepts, including parameter estimation, confidence intervals...
Applied Linear Regression for Longitudinal Data: With an Emphasis on Missing Observations
1st Edition
By Frans E.S. Tan, Shahab Jolani
December 09, 2022
This book introduces best practices in longitudinal data analysis at intermediate level, with a minimum number of formulas without sacrificing depths. It meets the need to understand statistical concepts of longitudinal data analysis by visualizing important techniques instead of using abstract ...
Probability and Statistical Inference: From Basic Principles to Advanced Models
1st Edition
By Miltiadis C. Mavrakakis, Jeremy Penzer
September 26, 2022
Probability and Statistical Inference: From Basic Principles to Advanced Models covers aspects of probability, distribution theory, and inference that are fundamental to a proper understanding of data analysis and statistical modelling. It presents these topics in an accessible manner without ...
Randomization, Bootstrap and Monte Carlo Methods in Biology
4th Edition
By Bryan F.J. Manly, Jorge A. Navarro Alberto
April 29, 2022
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. Like its bestselling predecessors, the fourth edition of Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates a large number of statistical ...
Design and Analysis of Experiments and Observational Studies using R
1st Edition
By Nathan Taback
April 27, 2022
Introduction to Design and Analysis of Scientific Studies exposes undergraduate and graduate students to the foundations of classical experimental design and observational studies through a modern framework - The Rubin Causal Model. A causal inference framework is important in design, data ...
Bayes Rules!: An Introduction to Applied Bayesian Modeling
1st Edition
By Alicia A. Johnson, Miles Q. Ott, Mine Dogucu
March 04, 2022
An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, the book is an ideal resource for advanced ...
Bayesian Modeling and Computation in Python
1st Edition
By Osvaldo A. Martin, Ravin Kumar, Junpeng Lao
December 29, 2021
Bayesian Modeling and Computation in Python aims to help beginner Bayesian practitioners to become intermediate modelers. It uses a hands on approach with PyMC3, Tensorflow Probability, ArviZ and other libraries focusing on the practice of applied statistics with references to the underlying ...
Foundations of Statistics for Data Scientists: With R and Python
1st Edition
By Alan Agresti, Maria Kateri
November 30, 2021
Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data ...
Sampling: Design and Analysis
3rd Edition
By Sharon L. Lohr
November 30, 2021
"The level is appropriate for an upper-level undergraduate or graduate-level statistics major. Sampling: Design and Analysis (SDA) will also benefit a non-statistics major with a desire to understand the concepts of sampling from a finite population. A student with patience to delve into the rigor ...