SpringerAlerts on Statistics: New Textbooks, March 2010 Visit us at springer.com
New Textbooks in Statistics
Below is a short list of some of our newer Statistics textbooks, grouped by series.

See the bottom of this message for instructions on how to obtain an examination copy
Use R
2nd Edition
Bayesian Computation with R
This textbook introduces Bayesian modeling by the use of computation using the R language. The second edition contains several new topics, more illustrations and changes in the R code illustrations according to the latest edition of the LearnBayes package.

By Jim Albert
Introductory Time Series with R
This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation.

By Paul S. P. Cowpertwait, Andrew V. Metcalfe
Applied Statistical Genetics with R
The text covers key genetic data concepts and statistical principles, providing readers with a solid foundation in methods for candidate gene and genome-wide association studies

By Andrea S. Foulkes
R Through Excel
This book builds on RExcel, a free add-in for Excel. RExcel integrates R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and minimizing the distraction of learning a new programming language.

By Richard M. Heiberger, Eric Neuwirth
Introducing Monte Carlo Methods with R
This text covers the main tools used in statistical simulation from a programmer's point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.

By Christian Robert, George Casella
A Primer of Ecology with R
This text combines an introduction to the theoretical concepts in general ecology with the R programming language. The book starts with geometric growth and proceeds through stability of multispecies interactions and species-abundance distributions.

By M. Henry H. Stevens
A Beginner's Guide to R
The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. This book contains everything you need to know to get started with R.

By Alain F. Zuur, Elena N. Ieno, Erik H.W. G. Meesters
Springer Texts in Statistics
Fundamentals of Probability: A First Course
This text covers standard topics in introductory probability theory as well as a vast amount of optional, but important, material. The text contains numerous, diverse examples and will help prepare students for advanced courses and for the actuary exam.

By Anirban DasGupta
2nd Edition
An Intermediate Course in Probability
This text provides readers with a solid background of the basic results and methods in probability theory. This new edition offers updated content, one hundred additional problems, and a new chapter that provides an outlook on further areas.

By Allan Gut
A First Course in Bayesian Statistical Methods
This text provides a self-contained introduction to the theory and application of Bayesian statistical methods. It is accessible to readers having a familiarity with probability, yet allows advanced readers to grasp the ideas underlying these methods.

By Peter D. Hoff
A Modern Approach to Regression with R
This text focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models.

By Simon J. Sheather
Springer Series in Statistics
Principles and Theory for Data Mining and Machine Learning
This book is an introduction to data mining and machine learning. The presentation is detailed and includes proofs not readily available outside original sources. The orientation is conceptual and the main points are reinforced by computational comparisons.

By Bertrand Clarke, Ernest Fokoue, Hao Helen Zhang
2nd Edition
The Elements of Statistical Learning
This major new edition features many new topics, including graphical models, random forests, ensemble methods, and spectral clustering. There is also a chapter on methods for wide data (p bigger than n), including multiple testing and false discovery rates.

By Trevor Hastie, Robert Tibshirani, Jerome Friedman
Statistical Analysis of Network Data
This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data. The material is organized according to a statistical taxonomy, and the presentation entails a conscious balance of concepts versus mathematics.

By Eric D. Kolaczyk
Statistics and Computing
Computational Statistics
This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods. The book includes a large number of exercises.

By James E. Gentle
A SAS/IML Companion for Linear Models
The book contains examples of SAS code for many of the computations relevant to a linear models course. However, the SAS code in these examples automates the analytic formulas. The code for high-level procedures like PROC MIXED is included for comparison.

By Jamis J. Perrett
Also Available
Basic Concepts of Probability and Statistics in the Law
This text sets out basic statistical tools as they have been applied in actual legal disputes. Examples span diverse fields of law, such as identification evidence, mass torts, securities law, environmental regulation, and capital punishment, among others

By Michael O. Finkelstein
How to Obtain Evaluation Copies
Did you know that you can have free access to electronic editions of Springer textbooks?

Here's how:

To order an evaluation copy of any Statistics textbook, simply go the product page for that textbook and click the "Online Examination Copy" link. Complete the download instructions, and begin your reading!

And remember, if for some reason an eBook is not available, a print copy of the textbook will be sent.
Sincerely,

Linda Lorusso
Product Manager, Statistics
Springer