Causality is central to the understanding and use of data. Without an understanding of cause effect relationships, we cannot use data to answer questions as basic as, “Does this treatment harm or help patients?” But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding...(展开全部)

A nontechnical guide to the basic ideas of modern causal inference, with illustrations from health, the economy, and public policy. Which of two antiviral drugs does the most to save people infected with Ebola virus? Does a daily glass of wine prolong or shorten life? Does winning the lottery make you more or less likely to go bankrupt? How do you identify genes that cause dise...(展开全部)

An accessible and contemporary introduction to the methods for determining cause and effect in the social sciences Causal inference encompasses the tools that allow social scientists to determine what causes what. Economists—who generally can’t run controlled experiments to test and validate their hypotheses—apply these tools to observational data to make connections. In a mess...(展开全部)

Did mandatory busing programs in the 1970s increase the school achievement of disadvantaged minority youth? Does obtaining a college degree increase an individual's labor market earnings? Did the use of the butterfly ballot in some Florida counties in the 2000 presidential election cost Al Gore votes? If so, was the number of miscast votes sufficiently large to have altered th...(展开全部)

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mat...(展开全部)

WINNER OF THE 2005 DEGROOT PRIZE! This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory...(展开全部)

[美] 德内拉•梅多斯  世界上最伟大的系统思考大师之一，师从系统动力学创始人杰伊•福瑞斯特，是知名的“世界模型Ⅲ”主创人员，也是 “学习型组织之父”、《第五项修炼》作者彼得•圣吉的老师。  1972年，作为畅销书《增长的极限》的第一作者，她引领了社会观念变革的先河，引发了全球对地球承载能力和人类选择的大辩论，另著有9本关于全球建模和可持续发展问题的著作，并于1996年创立了可持续性发展协会。  她始终处于环境与社会分析研究领域的最前沿，1991年被授予环境保护领域的“皮尤学者奖”，1994年又荣获“麦克阿瑟天才奖”。  从1972年直到2001年去世，她一直在达特茅斯学院环境研究项目任教，致力于在经济学、环境和社会变革等领域应用系统思考和组织学习的方法。