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 C.E. Weatherburn - Cambridge University Press
This book provides the mathematical foundations of statistics. It explains the principles, and proves the formulae to give validity to the methods of the interpretation of statistical data. It is of interest to students of a wide variety of subjects.
by David Lane - Rice University
This is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.
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 Alex Reinhart - refsmmat.com
This is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. It assumes no prior knowledge of statistics, you can read it before your first statistics course.