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Markov Decision Processes: Discrete Stochastic Dynamic Programming

by Martin L. Puterman

The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover...


Structural Equations with Latent Variables

by Kenneth A. Bollen

Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike...


Statistical Analysis with Missing Data

by Roderick J. A. Little & Donald B. Rubin

Praise for the First Edition of Statistical Analysis with Missing Data

"An important contribution to the applied statistics literature.... I give the book high marks for unifying and making accessible much of...


Applied Regression Analysis

by Norman R. Draper & Harry Smith

An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among...


Biostatistical Methods: The Assessment of Relative Risks

by John M. Lachin

Praise for the First Edition

". . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists."

International Statistical Institute

A new edition of the definitive guide...


Understanding Educational Statistics Using Microsoft Excel and SPSS

by Martin Lee Abbott

Utilizing the latest software, this book presents the essential statistical procedures for drawing valuable results from data in the social sciences.

Mobilizing interesting real-world examples from the field...


An Introduction to Bootstrap Methods with Applications to R

by Michael R. Chernick & Robert A. LaBudde

A comprehensive introduction to bootstrap methods in the R programming environment

Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard...


Log-Linear Modeling: Concepts, Interpretation, and Application

by Alexander von Eye & Eun-Young Mun

An easily accessible introduction to log-linear modeling for non-statisticians

Highlighting advances that have lent to the topic's distinct, coherent methodology over the past decade, Log-Linear Modeling: Concepts,...


Growth Curve Modeling: Theory and Applications

by Michael J. Panik

Features recent trends and advances in the theory and techniques used to accurately measure and model growth

Growth Curve Modeling: Theory and Applications features an accessible introduction to growth curve...


Super Golfonomics

by A01

Super Golfonomics continues along the path of Professor Shmanske's pathbreaking Golfonomics. It uses economic and statistical analysis of the sport of golf for three main purposes, (1) For the enjoyment of golfers...


Hidden Markov Processes: Theory and Applications to Biology

by M. Vidyasagar

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. The book starts from first principles, so that no...


The Fitness of Information: Quantitative Assessments of Critical Evidence

by Chaomei Chen

Theories and practices to assess critical information in a complex adaptive system

Organized for readers to follow along easily, The Fitness of Information: Quantitative Assessments of Critical Evidence provides...


Cognitive Interviewing Methodology: A Sociological Approach for Survey Question Evaluation

by Kristen Miller, Valerie Chepp & Stephanie Willson

AN INTERDISCIPLINARY PERSPECTIVE TO THE EVOLUTION OF THEORY AND METHODOLOGY WITHIN COGNITIVE INTERVIEW PROCESSES

Providing a comprehensive approach to cognitive interviewing in the field of survey methodology,...


Hands-On Programming with R: Write Your Own Functions and Simulations

by Garrett Grolemund

Learn how to program by diving into the R language, and then use your newfound skills to solve practical data science problems. With this book, you’ll learn how to load data, assemble and disassemble data...


Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining

by Glenn J. Myatt & Wayne P. Johnson

Praise for the First Edition

 “...a well-written book on data analysis and data mining that provides an excellent foundation...”

—CHOICE

“This is a must-read book for learning practical statistics and...


Finite Markov Processes and Their Applications

by Marius Iosifescu

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu, vice president of the Romanian Academy and director of its Center for...


Statistics for Exercise Science and Health with Microsoft Office Excel

by J. P. Verma

This book introduces the use of statistics to solve a variety of problems in exercise science and health and provides readers with a solid foundation for future research and data analysis.

Statistics for Exercise...


Probability 1

by Ph.D., Amir D. Aczel

For thousands of years, it was the visionaries and writers who argued that we cannot be alone-that there is intellegent life in the universe. Now, with the discoveries of the Hubble Telescope, data emerging...


Willful Ignorance: The Mismeasure of Uncertainty

by Herbert I. Weisberg

An original account of willful ignorance and how this principle relates to modern probability and statistical methods

Through a series of colorful stories about great thinkers and the problems they chose to...


Basic Data Analysis for Time Series with R

by DeWayne R. Derryberry

Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing...