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Introduction to Statistics through Resampling Methods and R/SPlus is a little "To Go" book tightly packed to provide a reader with the basics of statistical methods via resampling methods. The first part of the book is an introduction to statistics describing basic data summary statistics, the concept of probability, and distributions. Estimation, testing statistical hypothesis and model building comprise the rest of the book. Statistical concepts (such as hypothesis testing, etc.) are not explained from theoretical point of view at all, but rather through examples and author's "dialogue" with the reader. Even the concept of resampling is not explained to some technical degree of "statistical significance". The book is written in a narrative style and is not technical at all. There are some equations but compared to most introductory statistics texts this can be classified almost as a general reading.
As far as prerequisites for reading the book, high school algebra is enough. Some knowledge of R would be an advantage, and of course an interest in statistics is crucial. An adequate introduction to R and SPlus can be found in the programs' help files. These should be enough to get acquainted with the basics, which is enough to get started with this book. An SPlus appendix in the book gives a very slim introduction to SPlus, which I think is not enough to grasp even the main concepts of the software. To enable easier study, the complete R code presented in the book can be downloaded from the author's web site.
This book is very similar a "trial and error" type of task, where the reader is encouraged to try for oneself the examples in R. The reader is also encouraged to gather some samples on his own and try the methods presented. Exercises form a major part of the book; they are scattered throughout the text. Most of the exercises are computer based, i.e. they should be solved with the aid of R.
I would recommend this book to readers new to statistics, practitioners who lack the basics of statistical estimation and hypothesis testing, and students who need a side reference to help them in their more concrete study of statistical methods.
Ita Cirovic Donev is a PhD candidate at the University of Zagreb. She hold a Masters degree in statistics from Rice University. Her main research areas are in mathematical finance; more precisely, statistical mehods of credit and market risk. Apart from the academic work she does consulting work for financial institutions.
