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, Statistics, and Data: A Fresh Approach Using R
1st Edition
By Darrin Speegle, Bryan Clair
November 26, 2021
This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation. The book introduces probability with Monte Carlo simulation as an essential tool. Simulation makes challenging probability questions ...
Fundamentals of Causal Inference: With R
1st Edition
By Babette A. Brumback
November 10, 2021
"Overall, this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference. Each chapter provides an R implementation of the introduced causal concepts and models and concludes with appropriate exercises."-An-Shun Tai &...
A First Course in Linear Model Theory
2nd Edition
By Nalini Ravishanker, Zhiyi Chi, Dipak K. Dey
October 19, 2021
Thoroughly updated throughout, A First Course in Linear Model Theory, Second Edition is an intermediate-level statistics text that fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. With an ...
Statistical Analysis of Financial Data: With Examples In R
1st Edition
By James Gentle
September 30, 2021
Statistical Analysis of Financial Data covers the use of statistical analysis and the methods of data science to model and analyze financial data. The first chapter is an overview of financial markets, describing the market operations and using exploratory data analysis to illustrate the nature of ...
Bayesian Networks: With Examples in R
2nd Edition
By Marco Scutari, Jean-Baptiste Denis
July 29, 2021
Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss side by side the underlying theory and its application using R code. The examples start from the ...
Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects
1st Edition
By James S. Hodges
June 30, 2021
A First Step toward a Unified Theory of Richly Parameterized Linear Models Using mixed linear models to analyze data often leads to results that are mysterious, inconvenient, or wrong. Further compounding the problem, statisticians lack a cohesive resource to acquire a systematic, theory-based ...
Modern Data Science with R
2nd Edition
By Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
April 14, 2021
From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American ...
Bayesian Thinking in Biostatistics
1st Edition
By Gary L Rosner, Purushottam W. Laud, Wesley O. Johnson
March 16, 2021
Praise for Bayesian Thinking in Biostatistics: "This thoroughly modern Bayesian book …is a 'must have' as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of ...
Linear Models with Python
1st Edition
By Julian J. Faraway
December 28, 2020
Praise for Linear Models with R: This book is a must-have tool for anyone interested in understanding and applying linear models. The logical ordering of the chapters is well thought out and portrays Faraway’s wealth of experience in teaching and using linear models. … It lays down the material in ...
An Introduction to Nonparametric Statistics
1st Edition
By John E. Kolassa
September 29, 2020
An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques ...
Statistical Machine Learning: A Unified Framework
1st Edition
By Richard Golden
July 02, 2020
The recent rapid growth in the variety and complexity of new machine learning architectures requires the development of improved methods for designing, analyzing, evaluating, and communicating machine learning technologies. Statistical Machine Learning: A Unified Framework provides students, ...
Statistical Rethinking: A Bayesian Course with Examples in R and STAN
2nd Edition
By Richard McElreath
March 16, 2020
Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA) Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based ...