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  • Statistics

    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

March 25, 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...

Introductory Statistics for the Health Sciences

Introductory Statistics for the Health Sciences

Lise DeShea, Larry E. Toothaker

March 23, 2015

Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets...

Design and Analysis of Clinical Trials for Predictive Medicine

Design and Analysis of Clinical Trials for Predictive Medicine

Shigeyuki Matsui, Marc Buyse, Richard Simon

March 19, 2015

Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics—from identifying...

Statistical Reinforcement Learning: Modern Machine Learning Approaches

Statistical Reinforcement Learning: Modern Machine Learning Approaches

Masashi Sugiyama

March 16, 2015

Reinforcement learning is a mathematical framework for developing computer agents that can learn an optimal behavior by relating generic reward signals with its past actions. With numerous successful applications in business intelligence, plant control, and gaming, the RL framework is ideal for...

Pareto Distributions Second Edition

Pareto Distributions Second Edition

Barry C. Arnold

March 10, 2015

Since the publication of the first edition over 30 years ago, the literature related to Pareto distributions has flourished to encompass computer-based inference methods. Pareto Distributions, Second Edition provides broad, up-to-date coverage of the Pareto model and its extensions. This edition...

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition

Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition

Nicholas J. Horton, Ken Kleinman

March 10, 2015

Improve Your Analytical Skills Incorporating the latest R packages as well as new case studies and applications, Using R and RStudio for Data Management, Statistical Analysis, and Graphics, Second Edition covers the aspects of R most often used by statistical analysts. New users of R will find the...

Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation

Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation

Stephen Burgess, Simon G. Thompson

March 06, 2015

Presents the Terminology and Methods of Mendelian Randomization for Epidemiological Studies Mendelian randomization uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk...

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...

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