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Probability and Stochastic Processes

by Ionut Florescu

A comprehensive and accessible presentation of probability and stochastic processes with emphasis on key theoretical concepts and real-world applications

With a sophisticated approach, Probability and Stochastic...

Even You Can Learn Statistics and Analytics: An Easy to Understand Guide to Statistics and Analytics

by David M. Levine & David F. Stephan

Thought you couldn’t learn statistics? You can – and you will! Even You Can Learn Statistics and Analytics, Third Edition is the practical, up-to-date introduction to statistics – for everyone! Now fully...

Handbook of Statistics: Computational Statistics with R

by Marepalli B. Rao & C.R. Rao

R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available...

Machine Learning: Hands-On for Developers and Technical Professionals

by Jason Bell

Dig deep into the data with a hands-on guide to machine learning

Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most...

Statistical Inference for Models with Multivariate t-Distributed Errors

by A. K. Md. Ehsanes Saleh, Mohammad Arashi & S M M Tabatabaey

This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors:

  • Includes a wide array of...

An Introduction to Probability and Statistical Inference

by George G. Roussas

Probability models, statistical methods, and the information to be gained from them is vital for work in business, engineering, sciences (including social and behavioral), and other fields. Data must be properly...

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...

Benford's Law: Theory, the General Law of Relative Quantities, and Forensic Fraud Detection Applications

by Alex Ely Kossovsky

Contrary to common intuition that all digits should occur randomly with equal chances in real data, empirical examinations consistently show that not all digits are created equal, but rather that low digits...

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...

Probabilistic Normed Spaces

by Bernardo Lafuerza Guillen & Panackal Harikrishnan

This book provides a comprehensive foundation in Probabilistic Normed (PN) Spaces for anyone conducting research in this field of mathematics and statistics. It is the first to fully discuss the developments...

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...