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Chapman & Hall/CRC Texts in Statistical Science

Series Editor: Julian J. Faraway, Martin A. Tanner, Bradley. P. Carlin, Jim Zidek, Francesca Dominici

New and Published Books

1-10 of 89 results in Chapman & Hall/CRC Texts in Statistical Science
  1. Statistical Inference

    An Integrated Approach, Second Edition

    By Helio S. Migon, Dani Gamerman, Francisco Louzada

    Series: Chapman & Hall/CRC Texts in Statistical Science

    A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on...

    Published September 3rd 2014 by Chapman and Hall/CRC

  2. Analysis of Categorical Data with R

    By Christopher R. Bilder, Thomas M. Loughin

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Learn How to Properly Analyze Categorical DataAnalysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses...

    Published August 11th 2014 by Chapman and Hall/CRC

  3. Introduction to Probability

    By Joseph K. Blitzstein, Jessica Hwang

    Series: Chapman & Hall/CRC Texts in Statistical Science

    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...

    Published August 6th 2014 by Chapman and Hall/CRC

  4. Linear Models with R, Second Edition

    By Julian J. Faraway

    Series: Chapman & Hall/CRC Texts in Statistical Science

    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...

    Published July 1st 2014 by Chapman and Hall/CRC

  5. Bayesian Networks

    With Examples in R

    By Marco Scutari, Jean-Baptiste Denis

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Understand the Foundations of Bayesian Networks—Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the...

    Published June 20th 2014 by Chapman and Hall/CRC

  6. Linear Algebra and Matrix Analysis for Statistics

    By Sudipto Banerjee, Anindya Roy

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge...

    Published June 6th 2014 by Chapman and Hall/CRC

  7. Introduction to Multivariate Analysis

    Linear and Nonlinear Modeling

    By Sadanori Konishi

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random...

    Published June 6th 2014 by Chapman and Hall/CRC

  8. Stochastic Modeling and Mathematical Statistics

    A Text for Statisticians and Quantitative Scientists

    By Francisco J. Samaniego

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Provides a Solid Foundation for Statistical Modeling and Inference and Demonstrates Its Breadth of Applicability Stochastic Modeling and Mathematical Statistics: A Text for Statisticians and Quantitative Scientists addresses core issues in post-calculus probability and statistics in a way that is...

    Published January 14th 2014 by Chapman and Hall/CRC

  9. Nonlinear Time Series

    Theory, Methods and Applications with R Examples

    By Randal Douc, Eric Moulines, David Stoffer

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Designed for researchers and students, Nonlinear Times Series: Theory, Methods and Applications with R Examples familiarizes readers with the principles behind nonlinear time series models—without overwhelming them with difficult mathematical developments. By focusing on basic principles and theory...

    Published January 6th 2014 by Chapman and Hall/CRC

  10. Epidemiology

    Study Design and Data Analysis, Third Edition

    By Mark Woodward

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of...

    Published December 19th 2013 by Chapman and Hall/CRC