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Chapman & Hall/CRC Texts in Statistical Science


About the 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.

129 Series Titles

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Principles of Uncertainty

Principles of Uncertainty

2nd Edition

By Joseph B. Kadane
August 21, 2020

Praise for the first edition: Principles of Uncertainty is a profound and mesmerising book on the foundations and principles of subjectivist or behaviouristic Bayesian analysis. … the book is a pleasure to read. And highly recommended for teaching as it can be used at many different levels. … A ...

An Introduction to Nonparametric Statistics

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

Statistical Machine Learning: A Unified Framework

1st Edition

By Richard Golden
July 14, 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

Statistical Rethinking: A Bayesian Course with Examples in R and STAN

2nd Edition

By Richard McElreath
March 17, 2020

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 statistics, the book pushes you to perform step-by-step calculations that are usually automated. ...

Surrogates Gaussian Process Modeling, Design, and Optimization for the Applied Sciences

Surrogates: Gaussian Process Modeling, Design, and Optimization for the Applied Sciences

1st Edition

By Robert B. Gramacy
January 13, 2020

Surrogates: a graduate textbook, or professional handbook, on topics at the interface between machine learning, spatial statistics, computer simulation, meta-modeling (i.e., emulation), design of experiments, and optimization. Experimentation through simulation, "human out-of-the-loop" statistical ...

Probability and Bayesian Modeling

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 First Course with Bootstrap Starter

Time Series: A First Course with Bootstrap Starter

1st Edition

By Tucker S. McElroy, Dimitris N. Politis
December 05, 2019

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.S. ...

Practical Multivariate Analysis

Practical Multivariate Analysis

6th Edition

By Abdelmonem Afifi, Susanne May, Robin Donatello, Virginia A. Clark
October 08, 2019

This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business...

Time Series A Data Analysis Approach Using R

Time Series: A Data Analysis Approach Using R

1st Edition

By Robert Shumway, David Stoffer
May 20, 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

The Analysis of Time Series: An Introduction with R

7th Edition

By Chris Chatfield, Haipeng Xing
May 07, 2019

v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Kabra, Mansi Kabra, Mansi 2 1 2022-02-18T07:16:00Z 2022-02-18T07:16:00Z 1 182 1043 8 2 1223 16.00 true 2022-02-18T07:16...

Bayesian Statistical Methods

Bayesian Statistical Methods

1st Edition

By Brian J. Reich, Sujit K. Ghosh
April 11, 2019

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (...

Theory of Spatial Statistics A Concise Introduction

Theory of Spatial Statistics: A Concise Introduction

1st Edition

By M.N.M. van Lieshout
March 05, 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, ...

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