For those of us that want to keep up with the latest in the world of statistics here is a great list of 40 statistical blogs on the internet today from bschool.com. Some of the blogs even include R (link) which is my favorite statistical computing environment.
I have a few that I read on an occasional basis. Those include
R-Bloggers - an R blog aggregator that is very useful for R enthusiasists
Revolutions - blog by David Smith of Revolution Analytics, an enterprise ready R support and developer company
The Numbers Guy - Wall Street Journal blog about, you guessed it, numbers and statistics.
As you can tell I have been doing a lot of statistical work lately. Most of my efforts have been in the realm of predictive analytics. These blogs have come in useful in finding valuable references for predictive analytics. One book that is often mentioned in these statistical blogs is Applied logistic regression (Wiley Series in probability and statistics). I highly recommend this book as a statistical reference for logistic regression analysis.
Applied Logistic Regression takes the reader through an understanding logistic regression model and its usage for modern prediction analysis. The book starts with and understanding of log odds and introduction to the logistic regression model. Then the book goes into detail of the model parameters, coefficients, and estimation. Strategies for model building and case studies are also referred in this book.