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 Ivan Lowe - scientificlanguage.com
The book begins by expanding on some of the basic concepts such data types and variables. The basic choice then is between the family of statistics which compares groups, and the family which studies associations or correlations.
by Keijo Ruohonen - Tampere University of Technology
Table of contents: Fundamental sampling distributions and data descriptions; One- and two-sample estimation; Tests of hypotheses; X2-tests; Maximum likelihood estimation; Multiple linear regression; Nonparametric statistics; Stochastic simulation.
by Denis Anthony - BookBoon
This is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life, or social science who has no knowledge of statistics.
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.