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.
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...
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...
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...
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...
Vladimir I. Rotar
March 15, 2015
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...
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...
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...
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...
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...
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...
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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