Skip to Content

Books by Subject

Statistics & Computing Books

You are currently browsing 21–30 of 165 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 3

  1. Discovering Structural Equation Modeling Using Stata 13 (Revised Edition)

    By Alan C. Acock

    Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata’s sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each...

    Published September 9th 2013 by Stata Press

  2. Nonparametric Methods in Statistics with SAS Applications

    By Olga Korosteleva

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Designed for a graduate course in applied statistics, Nonparametric Methods in Statistics with SAS Applications teaches students how to apply nonparametric techniques to statistical data. It starts with the tests of hypotheses and moves on to regression modeling, time-to-event analysis, density...

    Published August 18th 2013 by Chapman and Hall/CRC

  3. Probability and Statistics for Computer Scientists, Second Edition

    By Michael Baron

    Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of...

    Published August 4th 2013 by Chapman and Hall/CRC

  4. Dynamic Documents with R and knitr

    By Yihui Xie

    Series: Chapman & Hall/CRC The R Series

    The cut-and-paste approach to writing statistical reports is not only tedious and laborious, but also can be harmful to scientific research, because it is inconvenient to reproduce the results. Dynamic Documents with R and knitr introduces a new approach via dynamic documents, i.e. integrating...

    Published July 25th 2013 by Chapman and Hall/CRC

  5. Statistical Methods for Handling Incomplete Data

    By Jae Kwang Kim, Jun Shao

    Due to recent theoretical findings and advances in statistical computing, there has been a rapid development of techniques and applications in the area of missing data analysis. Statistical Methods for Handling Incomplete Data covers the most up-to-date statistical theories and computational...

    Published July 22nd 2013 by Chapman and Hall/CRC

  6. Reproducible Research with R and RStudio

    By Christopher Gandrud

    Series: Chapman & Hall/CRC The R Series

    Bringing together computational research tools in one accessible source, Reproducible Research with R and RStudio guides you in creating dynamic and highly reproducible research. Suitable for researchers in any quantitative empirical discipline, it presents practical tools for data collection, data...

    Published July 14th 2013 by Chapman and Hall/CRC

  7. Analysis of Variance for Functional Data

    By Jin-Ting Zhang

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

    Despite research interest in functional data analysis in the last three decades, few books are available on the subject. Filling this gap, Analysis of Variance for Functional Data presents up-to-date hypothesis testing methods for functional data analysis. The book covers the reconstruction of...

    Published June 17th 2013 by Chapman and Hall/CRC

  8. Methods of Statistical Model Estimation

    By Joseph M. Hilbe, Andrew P. Robinson

    Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for...

    Published May 27th 2013 by Chapman and Hall/CRC

  9. Mean Field Simulation for Monte Carlo Integration

    By Pierre Del Moral

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

    In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to...

    Published May 19th 2013 by Chapman and Hall/CRC

  10. Applied Meta-Analysis with R

    By Ding-Geng (Din) Chen, Karl E. Peace

    Series: Chapman & Hall/CRC Biostatistics Series

    In biostatistical research and courses, practitioners and students often lack a thorough understanding of how to apply statistical methods to synthesize biomedical and clinical trial data. Filling this knowledge gap, Applied Meta-Analysis with R shows how to implement statistical meta-analysis...

    Published May 2nd 2013 by Chapman and Hall/CRC