Skip to Content

Books by Subject

Statistics Books

You are currently browsing 1–10 of 752 new and published books in the subject of Statistics — 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

  1. Current Trends in Bayesian Methodology with Applications

    Edited by Satyanshu K. Upadhyay, Umesh Singh, Dipak K. Dey, Appaia Loganathan

    Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics,...

    Published May 21st 2015 by Chapman and Hall/CRC

  2. Graphical Data Analysis with R

    By Antony Unwin

    Series: Chapman & Hall/CRC The R Series

    See How Graphics Reveal Information Graphical Data Analysis with R shows you what information you can gain from graphical displays. The book focuses on why you draw graphics to display data and which graphics to draw (and uses R to do so). All the datasets are available in R or one of its packages...

    Published May 20th 2015 by Chapman and Hall/CRC

  3. Understanding Political Science Statistics and Understanding PS Stats using STATA (bundle)

    By Peter Galderisi

    By emphasizing the underlying logic of statistical analysis for greater understanding and drawing on applications and examples from political science, Understanding Political Science Statistics illustrates how students can apply statistical concepts and techniques in their own research, in future...

    Published May 15th 2015 by Routledge

  4. Statistical Learning with Sparsity

    The Lasso and Generalizations

    By Trevor Hastie, Robert Tibshirani, Martin Wainwright

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

    Discover New Methods for Dealing with High-Dimensional Data A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents...

    Published May 7th 2015 by Chapman and Hall/CRC

  5. The Geometry of Multivariate Statistics

    By Thomas D. Wickens

    A traditional approach to developing multivariate statistical theory is algebraic. Sets of observations are represented by matrices, linear combinations are formed from these matrices by multiplying them by coefficient matrices, and useful statistics are found by imposing various criteria of...

    Published May 7th 2015 by Psychology Press

  6. Modelling Interactions Between Vector-Borne Diseases and Environment Using GIS

    By Hassan M. Khormi, Lalit Kumar

    Master GIS Applications on Modelling and Mapping the Risks of Diseases Infections transmitted by mosquitoes, ticks, triatomine bugs, sandflies, and black flies cause significant rates of death and disease, especially in developing countries. Why are certain places more susceptible to vector-borne...

    Published May 1st 2015 by CRC Press

  7. Understanding Politics Science Statistics and Understanding PS Statistics Using SPSS BUNDLE

    By Peter Galderisi

    By emphasizing the underlying logic of statistical analysis for greater understanding and drawing on applications and examples from political science, Understanding Political Science Statistics illustrates how students can apply statistical concepts and techniques in their own research, in future...

    Published April 29th 2015 by Routledge

  8. Modeling to Inform Infectious Disease Control

    By Niels G. Becker

    Series: Chapman & Hall/CRC Biostatistics Series

    Effectively Assess Intervention Options for Controlling Infectious Diseases Our experiences with the human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and Ebola virus disease (EVD) remind us of the continuing need to be vigilant against the emergence of new infectious...

    Published April 28th 2015 by Chapman and Hall/CRC

  9. Data Science in R

    A Case Studies Approach to Computational Reasoning and Problem Solving

    By Deborah Nolan, Duncan Temple Lang

    Series: Chapman & Hall/CRC The R Series

    Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the...

    Published April 21st 2015 by Chapman and Hall/CRC

  10. Robust Methods for Data Reduction

    By Alessio Farcomeni, Luca Greco

    Robust Methods for Data Reduction gives a non-technical overview of robust data reduction techniques, encouraging the use of these important and useful methods in practical applications. The main areas covered include principal components analysis, sparse principal component analysis, canonical...

    Published April 16th 2015 by Chapman and Hall/CRC