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.
Statistics is the study of the collection, analysis, interpretation, presentation and organization of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.
by Wolfgang K. Hardle, Leopold Simar - Springer
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
by Barbara Illowsky, Susan Dean - Illowsky Publising
Intended for introductory statistics courses for students at two and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications rather than the theory.