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 Douglas S. Shafer, Zhiyi Zhang - lardbucket.org
This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students. Our motivation for writing it is to provide a low-cost alternative to many existing popular textbooks on the market.
by James E. Gentle - George Mason University
This document is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations.
by D.M. Diez, C.D. Barr, M. Cetinkaya-Rundel - OpenIntro
OpenIntro Statistics is intended for introductory statistics courses at the high school through university levels. There are a large selection of exercises at the end of each chapter useful for practice or homework assignments.
by Jonathan A. Poritz - Colorado State University, Pueblo
This is a first draft of a free textbook for a one-semester, undergraduate statistics course. Contents: One-Variable Statistics - Basics; Bi-variate Statistics - Basics; Linear Regression; Probability Theory; Bringing Home the Data; Basic Inferences.