I stumbled on to this book way back in September 2010 and had been intending to work on frequency domain aspect of time series since then. I am embarrassed to admit that almost 2 years have passed since then and it was lying in my inventory crying to be picked up. Why did I put off reading this book for so long a time? May be, I am not managing my time properly.

Introduction The author begins the book with a slew of examples involving predictions that never materialized. These examples span a wide range of fields like economics, social sciences, finance, politics, etc. The author also sneaks in examples of his parents and grandparents lives to show how their lives panned out in ways that were completely unpredictable. Well, Do these examples prove anything ? You can quote volumes of predictions going wrong , but if you ask the people who predicted them, they always seem to have a defense.

As early as 1997, the financial markets comprised blue chip stocks traded by specialists at NYSE , other stocks traded at NASDAQ by specialists and a small scale electronic system. Fast forward to 2012, the US market comprises 40 trading destinations. There are four public exchanges - NYSE, NASDAQ, Direct Edge and BATS. Inside each of these exchanges there are various destinations. NYSE has NYSE Arca, NYSE Amex, NYSE Euro next and NYSE Alternext, NASDAQ has three markets, BATS and Direct Edge have two market destinations with in themselves.

[The book is written by Julian Faraway , a Statistics Professor at University of Bath. The book seems to be culmination of lecture notes that the professor might have used over the years for teaching linear models. Whatever be the case, the book is wonderfully organized. If you already know the math behind linear models, the book does exactly as it promises in the title,i.e, it equips the reader to do linear modeling in R.

The love of theory is the root of all evil. ** _--** William M. Briggs_