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Statistics & Computing Books

You are currently browsing 81–90 of 164 new and published books in the subject of Statistics & Computing — sorted by publish date from newer books to older books.

For books that are not yet published; please browse forthcoming books.

New and Published Books – Page 9

  1. Using R for Data Management, Statistical Analysis, and Graphics

    By Nicholas J. Horton, Ken Kleinman

    Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics Using R for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in R, without having to navigate...

    Published July 28th 2010 by CRC Press

  2. Using SAS for Data Management, Statistical Analysis, and Graphics

    By Ken Kleinman, Nicholas J. Horton

    Quick and Easy Access to Key Elements of Documentation Includes worked examples across a wide variety of applications, tasks, and graphics A unique companion for statistical coders, Using SAS for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an...

    Published July 28th 2010 by CRC Press

  3. Multiple Comparisons Using R

    By Frank Bretz, Torsten Hothorn, Peter Westfall

    Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R. The R packages and source code...

    Published July 27th 2010 by Chapman and Hall/CRC

  4. Bayesian Ideas and Data Analysis

    An Introduction for Scientists and Statisticians

    By Ronald Christensen, Wesley Johnson, Adam Branscum, Timothy E Hanson

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions,...

    Published July 2nd 2010 by CRC Press

  5. Statistical Inference

    An Integrated Bayesian/Likelihood Approach

    By Murray Aitkin

    Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

    Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to...

    Published June 2nd 2010 by Chapman and Hall/CRC

  6. Data Management Using Stata

    A Practical Handbook

    By Michael N. Mitchell

    Using simple language and illustrative examples, this book comprehensively covers data management tasks that bridge the gap between raw data and statistical analysis. Rather than focus on clusters of commands, the author takes a modular approach that enables readers to quickly identify and...

    Published May 24th 2010 by Stata Press

  7. Time Series

    Modeling, Computation, and Inference

    By Raquel Prado, Mike West

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Focusing on Bayesian approaches and computations using simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It...

    Published May 21st 2010 by Chapman and Hall/CRC

  8. Relational Data Clustering

    Models, Algorithms, and Applications

    By Bo Long, Zhongfei Zhang, Philip S. Yu

    Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

    A culmination of the authors’ years of extensive research on this topic, Relational Data Clustering: Models, Algorithms, and Applications addresses the fundamentals and applications of relational data clustering. It describes theoretic models and algorithms and, through examples, shows how to apply...

    Published May 19th 2010 by Chapman and Hall/CRC

  9. Applied Bayesian Hierarchical Methods

    By Peter D. Congdon

    The use of Markov chain Monte Carlo (MCMC) methods for estimating hierarchical models involves complex data structures and is often described as a revolutionary development. An intermediate-level treatment of Bayesian hierarchical models and their applications, Applied Bayesian Hierarchical Methods...

    Published May 19th 2010 by Chapman and Hall/CRC

  10. Graphics for Statistics and Data Analysis with R

    By Kevin J Keen

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Graphics for Statistics and Data Analysis with R presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide array of graphical displays for the presentation of data, including modern tools...

    Published April 26th 2010 by Chapman and Hall/CRC