Introduction to Statistical Thought
by Michael Lavine
Number of pages: 434
Upper undergraduate or introductory graduate book in statistical thinking for students with a solid background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how statisticians put those ideas into practice. The book uses computer simulations written with the statistical language R, which is available for free download.
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by Miguel A. Hernan, James M. Robins - Chapman & Hall/CRC
The book provides a cohesive presentation of concepts of, and methods for, causal inference. It will be of interest to anyone interested in causal inference, e.g., epidemiologists, statisticians, psychologists, economists, sociologists, and others.
by Brian S Blais - Save The Broccoli Publishing
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester.
by David Lane - Rice University
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