This is a reissue of the book by statistician R.G. Miller. The text has proved useful in understanding the level of the subject of applied statistics and includes numerous exericises.

Data Driven Statistical Methods is designed for use either as a text book at the undergraduate level, as a source book providing material and suggestions for teachers wishing to incorporate some of its features into more general courses, and also as a self-instruction manual for applied statisticians seeking a simple introduction to many important practical concepts that use the 'data driven' rather than the 'model driven' approach.

Traditional texts in mathematical statistics can seem - to some reader s-heavily weighted with optimality theory of the various flavors devel oped in the 1940s and 50s, and not particularly relevant to statistical practice. Mathematical Statistics stands apart from these treatments. While mathematically rigorous, its focus is on providing a set of use ful tools that allow readers to understand the theoretical underpinnin gs of statistical methodology

Sampling Methodologies with Applications offers a balanced, practical treatment of the techniques and applications of the commonly used proc edures for sampling from finite populations. It keeps mathematics to a minimum, but does not avoid them entirely: it features the principle results within the text but provides their derivations in the Appendic es to each chapter. In an easily followed, step-by-step presentation, the author motivates each topic with illustrations followed by example s and exercises. All of these are constructed from everyday, practical situations covering a wide variety...

Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of "recipes."

Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing...