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Foundations of Linear and Generalized Linear Models

by Alan Agresti

A valuable overview of the most important ideas and results in statistical analysis

Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide...


Probability: An Introduction with Statistical Applications

by John J. Kinney

Praise for the First Edition

"This is a well-written and impressively presented introduction to probability and statistics. The text throughout is highly readable, and the author makes liberal use of graphs and...


Introductory Statistics and Analytics: A Resampling Perspective

by Peter C. Bruce

Concise, thoroughly class-tested primer that features basic statistical concepts in the concepts in the context of analytics, resampling, and the bootstrap

A uniquely developed presentation of key statistical...


Probabilities: The Little Numbers That Rule Our Lives

by Peter Olofsson

Praise for the First Edition

“If there is anything you want to know, or remind yourself, about probabilities, then look no further than this comprehensive, yet wittily written and enjoyable, compendium of how...


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

Providing core training in R for a successful career in statistics practice


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

    • Content, examples, an enhanced number of exercises, and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great...

    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...