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.
Home page url
Download or read it online for free here:
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.
by Philip B. Stark - University of California, Berkeley
This text was written for an introductory class in Statistics for students in Business, Economics, or Social Science. This is the first and last class in Statistics. It also covers logic and reasoning at a level suitable for a general course.
by Henk van Elst - arXiv
These lecture notes were written to provide an accessible though technically solid introduction to the logic of systematical analyses of statistical data to undergraduate and postgraduate students in the Social Sciences and Economics in particular.
by Joseph B. Kadane - Chapman and Hall/CRC
An accessible, comprehensive guide to the theory of Bayesian statistics, this book presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.