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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.

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Time Series: A First Course with Bootstrap Starter

Time Series: A First Course with Bootstrap Starter

1st Edition

Forthcoming

Tucker S. McElroy, Dimitris N. Politis
January 03, 2020

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....

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

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

1st Edition

Forthcoming

Robert B. Gramacy
January 03, 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

Forthcoming

Jim Albert, Jingchen Hu
December 17, 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...

Practical Multivariate Analysis

Practical Multivariate Analysis

6th Edition

Abdelmonem Afifi, Susanne May, Robin Donatello, Virginia A. Clark
October 14, 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

Robert Shumway, David 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

The Analysis of Time Series: An Introduction with R

7th Edition

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...

Bayesian Statistical Methods

Bayesian Statistical Methods

1st Edition

Brian J. Reich, Sujit K. Ghosh
April 16, 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 (...

Sampling: Design and Analysis

Sampling: Design and Analysis

2nd Edition

Sharon L. Lohr
April 09, 2019

This edition is a reprint of the second edition published by Cengage Learning, Inc. Reprinted with permission. What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and...

Theory of Spatial Statistics: A Concise Introduction

Theory of Spatial Statistics: A Concise Introduction

1st Edition

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

Introduction to Probability, Second Edition

2nd Edition

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...

Statistics in Engineering: With Examples in MATLAB® and R, Second Edition

Statistics in Engineering: With Examples in MATLAB® and R, Second Edition

2nd Edition

Andrew Metcalfe, David Green, Tony Greenfield, Mayhayaudin Mansor, Andrew Smith, Jonathan Tuke
January 29, 2019

Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering, Second Edition: With Examples in MATLAB and R covers the fundamentals of...

A Computational Approach to Statistical Learning

A Computational Approach to Statistical Learning

1st Edition

Taylor Arnold, Michael Kane, Bryan W. Lewis
January 29, 2019

A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal...

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