Statistics

Per Page:
Sort:

Modern Data Science with R

Featured

Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 2, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programmi...

Generalized Additive Models: An Introduction with R, Second Edition

Featured

Simon N. Wood
June 6, 2017

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary bac...

Testing R Code

Featured

Richard Cotton
January 19, 2017

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy...

Exploratory Data Analysis with MATLAB, Third Edition

Featured

Wendy L. Martinez, Angel R. Martinez, Jeffrey Solka
June 1, 2017

Praise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "Prac...

Errors, Blunders, and Lies: How to Tell the Difference

Featured

David Salsburg
April 19, 2017

We live in a world that is not quite "right." The central tenet of statistical inquiry is that Observation = Truth + Error because even the most careful of scientific investigations have always been bedeviled by uncertainty. Our attempts to measure things are plagued with small errors. Our attempt...

Bioassays with Arthropods, Third Edition

Jacqueline L. Robertson, Moneen Marie Jones, Efren Olguin, Brad Alberts
June 23, 2017

Imagine a statistics book for bioassays written by a statistician. Next, imagine a statistics book for bioassays written for a layman. Bioassays with Arthropods, Third Edition offers the best of both worlds by translating the terse, precise language of the statistician into language used by the...

Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems

Jiming Jiang
June 15, 2017

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice....

Data Analysis Using Hierarchical Generalized Linear Models with R

Youngjo Lee, Lars Ronnegard, Maengseok Noh
June 15, 2017

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the...

Computational Methods for Numerical Analysis with R

James P Howard, II
June 12, 2017

Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code....

Clinical Trial Optimization Using R

Alex Dmitrienko, Erik Pulkstenis
June 12, 2017

Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with a powerful evaluation paradigm, as well as...

Generalized Additive Models: An Introduction with R, Second Edition

Simon N. Wood
June 06, 2017

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary...

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Youngjo Lee, John A. Nelder, Yudi Pawitan
June 05, 2017

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical...

Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics

Fionn Murtagh
June 05, 2017

"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in...

Exploratory Data Analysis with MATLAB, Third Edition

Wendy L. Martinez, Angel R. Martinez, Jeffrey Solka
June 01, 2017

Praise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "...

Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition

Bruce Ratner
June 01, 2017

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative...

Modern Statistics for the Social and Behavioral Sciences: A Practical Introduction, Second Edition

Rand Wilcox
May 30, 2017

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal...

Big Data Management and Processing

Kuan-Ching Li, Hai Jiang, Albert Y. Zomaya
May 25, 2017

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and...

Conferences

Year: