Recently, I have been reading two books which may be of interest to data miners, Statistical Rules of Thumb by Gerald Van Belle (ISBN-13: 978-0471402275) and Common Errors in Statistics (and How to Avoid Them), by by Phillip I. Good and James W. Hardin (ISBN-13: 978-0471794318). Both impart practical advice based on extensive experience and statistical rigor, yet avoid becoming hung up on academic issues.
While both are written from the point of view of traditional statisticians, they do suggest the use of some less traditional techniques, such as the bootstrap and robust regression. A wide range of topics is covered, such as sample size determination, hypothesis testing and treatment of missing values. Both books also include some material written for audiences working in specific fields, such as environmental science and epidemiology. Material in these two books will vary in applicability to data mining, given the traditional statistical focus on smaller data sets and parametric modeling.
I highly recommend both of them. Tables of contents can easily be found on-line, and an entire chapter of Statistical Rules of Thumb is available at: Chapter 2: Sample Size.