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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

41-50 of 88 results in Chapman & Hall/CRC Texts in Statistical Science
  1. A Primer on Linear Models

    By John F. Monahan

    Series: Chapman & Hall/CRC Texts in Statistical Science

    A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample...

    Published March 30th 2008 by Chapman and Hall/CRC

  2. Introduction to Probability with R

    By Kenneth Baclawski

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view....

    Published January 23rd 2008 by Chapman and Hall/CRC

  3. Time Series Analysis

    By Henrik Madsen

    Series: Chapman & Hall/CRC Texts in Statistical Science

    With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explores the connections among stochastic dynamic models. Emphasizing the time domain description, the...

    Published November 27th 2007 by Chapman and Hall/CRC

  4. Introduction to Statistical Methods for Clinical Trials

    By Thomas D. Cook, David L DeMets

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical...

    Published November 18th 2007 by Chapman and Hall/CRC

  5. Applied Nonparametric Statistical Methods, Fourth Edition

    By Peter Sprent, Nigel C. Smeeton

    Series: Chapman & Hall/CRC Texts in Statistical Science

    While preserving the clear, accessible style of previous editions, Applied Nonparametric Statistical Methods, Fourth Edition reflects the latest developments in computer-intensive methods that deal with intractable analytical problems and unwieldy data sets. Reorganized and with additional material...

    Published March 5th 2007 by Chapman and Hall/CRC

  6. Introduction to Randomized Controlled Clinical Trials, Second Edition

    By John N.S. Matthews

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Evidence from randomized controlled clinical trials is widely accepted as the only sound basis for assessing the efficacy of new medical treatments. Statistical methods play a key role in all stages of these trials, including their justification, design, and analysis. This second edition of...

    Published June 25th 2006 by Chapman and Hall/CRC

  7. Markov Chain Monte Carlo

    Stochastic Simulation for Bayesian Inference, Second Edition

    By Dani Gamerman, Hedibert F. Lopes

    Series: Chapman & Hall/CRC Texts in Statistical Science

    While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new...

    Published May 9th 2006 by Chapman and Hall/CRC

  8. Generalized Additive Models

    An Introduction with R

    By Simon Wood

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Now in widespread use, generalized additive models (GAMs) have evolved into a standard statistical methodology of considerable flexibility. While Hastie and Tibshirani's outstanding 1990 research monograph on GAMs is largely responsible for this, there has been a long-standing need for an...

    Published February 26th 2006 by Chapman and Hall/CRC

  9. Extending the Linear Model with R

    Generalized Linear, Mixed Effects and Nonparametric Regression Models

    By Julian J. Faraway

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Linear models are central to the practice of statistics and form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R examined regression and analysis of variance, demonstrated the different methods available, and showed in which...

    Published December 19th 2005 by Chapman and Hall/CRC

  10. Statistical Methods for Spatial Data Analysis

    By Oliver Schabenberger, Carol A. Gotway

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools...

    Published December 19th 2004 by Chapman and Hall/CRC