Statistics

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    The scope of the books in our Statistics collection is wide. The books encompass theory and methods, including Bayesian, spatial, regression, nonparametric, and multivariate techniques, as well as computational tools, such as R, SAS, Stata, and MATLAB®. The books also focus on key applications areas, such as medicine and epidemiology, genetics and bioinformatics, machine learning, data mining and Big Data, data science, reproducible research, the social and behavioral sciences, environmental science, business, finance, and economics.

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Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition

Peter .J. Bickel, Kjell A. Doksum

February 17, 2015

Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition presents fundamental, classical statistical concepts at the doctorate level. It covers estimation, prediction, testing, confidence sets, Bayesian analysis, and the general approach of decision theory. This edition...

Markov Processes

Markov Processes

James R. Kirkwood

February 09, 2015

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic processes and also as a reference for those that want to see detailed proofs of the theorems of Markov processes. It contains copious computational examples that...

Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures

Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures

Charlie Chunhua Liu

February 06, 2015

Create Top-Quality Figures Using SAS Producing High-Quality Figures Using SAS/GRAPH® and ODS Graphics Procedures gives statisticians and SAS programmers practical guidance on presenting research data in high-quality figures that meet the publication requirements of academic institutions and various...

Machine Translation

Machine Translation

Pushpak Bhattacharyya

January 13, 2015

Three paradigms have dominated machine translation (MT)—rule-based machine translation (RBMT), statistical machine translation (SMT), and example-based machine translation (EBMT). These paradigms differ in the way they handle the three fundamental processes in MT—analysis, transfer, and generation...

Quantitative Methods and Socio-Economic Applications in GIS, Second Edition

Quantitative Methods and Socio-Economic Applications in GIS, Second Edition

Fahui Wang

December 19, 2014

The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book...

Statistical Methods in Drug Combination Studies

Statistical Methods in Drug Combination Studies

Wei Zhao, Harry Yang

December 19, 2014

The growing interest in using combination drugs to treat various complex diseases has spawned the development of many novel statistical methodologies. The theoretical development, coupled with advances in statistical computing, makes it possible to apply these emerging statistical methods in in...

Design and Analysis of Experiments with R

Design and Analysis of Experiments with R

John Lawson

December 17, 2014

Design and Analysis of Experiments with R presents a unified treatment of experimental designs and design concepts commonly used in practice. It connects the objectives of research to the type of experimental design required, describes the process of creating the design and collecting the data,...

Introduction to High-Dimensional Statistics

Introduction to High-Dimensional Statistics

Christophe Giraud

December 17, 2014

Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing...

Statistics in MATLAB: A Primer

Statistics in MATLAB: A Primer

MoonJung Cho, Wendy L. Martinez

December 15, 2014

Fulfilling the need for a practical user’s guide, Statistics in MATLAB: A Primer provides an accessible introduction to the latest version of MATLAB® and its extensive functionality for statistics. Assuming a basic knowledge of statistics and probability as well as a fundamental understanding of...

Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition

Bayesian Methods: A Social and Behavioral Sciences Approach, Third Edition

Jeff Gill

December 11, 2014

An Update of the Most Popular Graduate-Level Introductions to Bayesian Statistics for Social Scientists Now that Bayesian modeling has become standard, MCMC is well understood and trusted, and computing power continues to increase, Bayesian Methods: A Social and Behavioral Sciences Approach, Third...

Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling

Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling

Heungsun Hwang, Yoshio Takane

December 11, 2014

Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the...

Inference Principles for Biostatisticians

Inference Principles for Biostatisticians

Ian C. Marschner

December 11, 2014

Designed for students training to become biostatisticians as well as practicing biostatisticians, Inference Principles for Biostatisticians presents the theoretical and conceptual foundations of biostatistics. It covers the theoretical underpinnings essential to understanding subsequent core...

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