by Miguel A. Hernan, James M. Robins
Publisher: Chapman & Hall/CRC 2015
Number of pages: 352
The book provides a cohesive presentation of concepts of, and methods for, causal inference. We expect that the book will be of interest to anyone interested in causal inference, e.g., epidemiologists, statisticians, psychologists, economists, sociologists, other social scientists... The book is geared towards graduate students and practitioners.
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by James E. Gentle - Springer
This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques that arise in a wide range of methods. The book assumes an intermediate background in mathematics, computing, and statistics.
by Philip B. Stark - University of California, Berkeley
This text was written for an introductory class in Statistics for students in Business, Economics, or Social Science. This is the first and last class in Statistics. It also covers logic and reasoning at a level suitable for a general course.
by David M Diez, et al. - OpenIntro
Statistics is an applied field with a wide range of practical applications. This book is geared to the high school audience and is specifically tailored to be aligned with the AP Statistics curriculum. It is already being used by many high schools.
by Irving W. Burr - McGraw-Hill
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.