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Statistics & Probability Books

You are currently browsing 41–50 of 946 new and published books in the subject of Statistics & Probability — sorted by publish date from newer books to older books.

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New and Published Books – Page 5

  1. 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

  2. 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

  3. Basic Gambling Mathematics

    The Numbers Behind The Neon

    By Mark Bollman

    Understand the Math Underlying Some of Your Favorite Gambling Games Basic Gambling Mathematics: The Numbers Behind the Neon explains the mathematics involved in analyzing games of chance, including casino games, horse racing, and lotteries. The book helps readers understand the mathematical...

    Published June 12th 2014 by Chapman and Hall/CRC

  4. Introduction to Scientific Programming and Simulation Using R, Second Edition

    By Owen Jones, Robert Maillardet, Andrew Robinson

    Series: Chapman & Hall/CRC The R Series

    Learn How to Program Stochastic Models Highly recommended, the best-selling first edition of Introduction to Scientific Programming and Simulation Using R was lauded as an excellent, easy-to-read introduction with extensive examples and exercises. This second edition continues to introduce...

    Published June 11th 2014 by Chapman and Hall/CRC

  5. Linear Algebra and Matrix Analysis for Statistics

    By Sudipto Banerjee, Anindya Roy

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge...

    Published June 5th 2014 by Chapman and Hall/CRC

  6. Introduction to Multivariate Analysis

    Linear and Nonlinear Modeling

    By Sadanori Konishi

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Select the Optimal Model for Interpreting Multivariate Data Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random...

    Published June 5th 2014 by Chapman and Hall/CRC

  7. Fixed Point Theory, Variational Analysis, and Optimization

    Edited by Saleh Abdullah R. Al-Mezel, Falleh Rajallah M. Al-Solamy, Qamrul Hasan Ansari

    Fixed Point Theory, Variational Analysis, and Optimization not only covers three vital branches of nonlinear analysis—fixed point theory, variational inequalities, and vector optimization—but also explains the connections between them, enabling the study of a general form of variational inequality...

    Published June 2nd 2014 by Chapman and Hall/CRC

  8. Robust Response Surfaces, Regression, and Positive Data Analyses

    By Rabindra Nath Das

    Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and...

    Published May 20th 2014 by Chapman and Hall/CRC

  9. Quantitative Finance

    A Simulation-Based Introduction Using Excel

    By Matt Davison

    Teach Your Students How to Become Successful Working Quants Quantitative Finance: A Simulation-Based Introduction Using Excel provides an introduction to financial mathematics for students in applied mathematics, financial engineering, actuarial science, and business administration. The text not...

    Published May 7th 2014 by Chapman and Hall/CRC

  10. Latent Variable Modeling Using R

    A Step-by-Step Guide

    By A. Alexander Beaujean

    This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected...

    Published May 5th 2014 by Routledge