Skip to Content

Books by Subject

Statistics & Probability Books

You are currently browsing 41–50 of 1,004 new and published books in the subject of Statistics & Probability — 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 5

  1. Data Analysis and Approximate Models

    Model Choice, Location-Scale, Analysis of Variance, Nonparametric Regression and Image Analysis

    By Patrick Laurie Davies

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

    The First Detailed Account of Statistical Analysis That Treats Models as Approximations The idea of truth plays a role in both Bayesian and frequentist statistics. The Bayesian concept of coherence is based on the fact that two different models or parameter values cannot both be true. Frequentist...

    Published July 6th 2014 by Chapman and Hall/CRC

  2. 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 June 30th 2014 by Chapman and Hall/CRC

  3. Dependence Modeling with Copulas

    By Harry Joe

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

    Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine...

    Published June 25th 2014 by Chapman and Hall/CRC

  4. Using R for Introductory Statistics, Second Edition

    By John Verzani

    Series: Chapman & Hall/CRC The R Series

    The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the...

    Published June 25th 2014 by Chapman and Hall/CRC

  5. A Handbook of Statistical Analyses using R, Third Edition

    By Torsten Hothorn, Brian S. Everitt

    Like the best-selling first two editions, A Handbook of Statistical Analyses using R, Third Edition provides an up-to-date guide to data analysis using the R system for statistical computing. The book explains how to conduct a range of statistical analyses, from simple inference to recursive...

    Published June 24th 2014 by Chapman and Hall/CRC

  6. Counterparty Risk and Funding

    A Tale of Two Puzzles

    By Stéphane Crépey, Tomasz R. Bielecki, Damiano Brigo

    Series: Chapman and Hall/CRC Financial Mathematics Series

    Solve the DVA/FVA Overlap Issue and Effectively Manage Portfolio Credit Risk Counterparty Risk and Funding: A Tale of Two Puzzles explains how to study risk embedded in financial transactions between the bank and its counterparty. The authors provide an analytical basis for the quantitative...

    Published June 22nd 2014 by Chapman and Hall/CRC

  7. Recursive Identification and Parameter Estimation

    By Han-Fu Chen, Wenxiao Zhao

    Recursive Identification and Parameter Estimation describes a recursive approach to solving system identification and parameter estimation problems arising from diverse areas. Supplying rigorous theoretical analysis, it presents the material and proposed algorithms in a manner that makes it easy to...

    Published June 22nd 2014 by CRC Press

  8. Modern Survey Sampling

    By Arijit Chaudhuri

    Starting from the preliminaries and ending with live examples, Modern Survey Sampling details what a sample can communicate about an unknowable aggregate in a real situation. The author lucidly develops and presents numerous approaches. He details recent developments and explores fresh and unseen...

    Published June 22nd 2014 by Chapman and Hall/CRC

  9. 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 19th 2014 by Chapman and Hall/CRC

  10. Multilevel Modeling Using R

    By W. Holmes Finch, Jocelyn E. Bolin, Ken Kelley

    Series: Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences

    A powerful tool for analyzing nested designs in a variety of fields, multilevel/hierarchical modeling allows researchers to account for data collected at multiple levels. Multilevel Modeling Using R provides you with a helpful guide to conducting multilevel data modeling using the R software...

    Published June 12th 2014 by CRC Press