Deciding it was time to finally learn statistics, I enrolled in 2, quarter-long Mathematical Statistics courses at the university where I was a chemistry professor.  The courses covered probability, the standard group of continuous and discrete distributions, confidence intervals, hypothesis testing, linear models, ANOVA, categorical data, and non-parametric statistics, and both courses used the Wackerly, et. al. text.<br><br>I believe that this book is designed to teach statistics to those who plan on actually using it professionally (and not just to pass a required course) while continuing to develop one's own mathematical maturity.  While Wackerly is not as rigorous as Ross's Probability book, it is taught at a completely different level than a non-calculus-based statistics course that are often taken by students who simply want to know which formula to use for the exam.  I think of it as the ideal text for anyone in the sciences, engineering, or economics.  The level of rigor is similar to the 2 Calculus courses online at MIT-Open Course Ware.<br><br>I found the book to be extremely well-written, while keeping each section fairly short, as the range of topics is fairly complete for a "classical" text--40% greater than what we covered in 2 quarters.  There are lots of practical plug-and-chug problems from the sciences / engineering / economics that are good at teaching you when exactly you should use one formula versus another.<br><br>Simultaneously, this book derives virtually every formula, allowing students to continue to develop their mathematical maturity which will be required for higher-level courses on bootstrapping, pattern recognition, statistical learning, etc.  In order to follow these proofs (and also in order to solve problems from about 4 chapters) one must have a firm grasp of calculus.  That not only means that one can integrate, differentiate, work with series, use L-Hopital's rule and integration-by-parts, but also that one understands the concepts of calculus very well.<br><br>The proofs are all broken down so as to not really skip many steps, but as someone away from math for over 25 years, I must write down each step myself and make sure that I understand it before moving on.  If a few steps are skipped, I must connect the dots myself using plenty of scratch paper.  My math background was the Calculus series, ordinary differential equations, and linear algebra.  About 1/5 of all problems are proof-based.<br><br>I highly recommend this book to anyone serious about learning statistics.