Statistical Models

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedma...

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

David A. Freedman（1938-2008）

加州大學(xué)伯克利分校的統(tǒng)計學(xué)教授。他是杰出的數(shù)理統(tǒng)計學(xué)家，其研究范圍包括鞅不等式分析、Markov過程、抽樣、自助法等。他是美國科學(xué)院院士。在2003年，他獲得了美國科學(xué)院授予的 John J.Carty 科學(xué)進(jìn)步獎，以表彰他對統(tǒng)計理論和實踐做出的貢獻(xiàn)。