
In this classic of statistical mathematical theory, Harald Cramer joins the two major lines of development in the field: while British and American statisticians were developing the science of statistical inference, French and Russian probabilitists transformed the classical calculus of probability into a rigorous and pure mathematical theory. The result of Cramer's work is a masterly exposition of the mathematical methods of modern statistics that set the standard that others have since sought to follow. For anyone with a working knowledge of undergraduate mathematics the book is self contained. The first part is an introduction to the fundamental concept of a distribution and of integration with respect to a distribution. The second part contains the general theory of random variables and probability distributions while the third is devoted to the theory of sampling, statistical estimation, and tests of significance. --back cover
The Mathematical Methods of Statistics by Harald Cramér is also excellent.
These are two very different approaches. Mathematical statistics goes trough measure theoretic probability, it connects statistics and mathematic and unifies the discrete and the continuous cases into a coherent whole.
Examples of both
- All of Statistics: A Concise Course in Statistical Inference by Wasserman
- Mathematical Methods of Statistics by Cramer