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Discrete Choice Methods with Simulation, by Kenneth Train, Cambridge University Press, 2002
"This electronic version of Discrete Choice Methods with Simulation is made available for use by individuals for their personal research and study. Permission is not granted to use any part of this work for any other purpose whatsoever without the express written consent of the Cambridge University Press. "
Elements of Statistical Learning: data mining, inference, and prediction. 2nd Edition.
Wow! PDF file of the whole book online, plus some R examples.
Networks, Crowds, and Markets: A Book by David Easley and Jon Kleinberg
"Networks, Crowds, and Markets combines different scientific perspectives in its approach to understanding networks and behavior. Drawing on ideas from economics, sociology, computing and information science, and applied mathematics, it describes the emerging field of study that is growing at the interface of all these areas, addressing fundamental questions about how the social, economic, and technological worlds are connected.
The book is based on an inter-disciplinary course entitled Networks that we teach at Cornell. The book, like the course, is designed at the introductory undergraduate level with no formal prerequisites. To support deeper explorations, most of the chapters are supplemented with optional advanced sections. "
Rough Type: Nicholas Carr's Blog: Close down the schools!
"Finally, it should be noted that, of the 51 experiments studied, only 11 actually showed a statistically significant advantage to online instruction."
CRAN - Package HybridMC
This package is an R implementation of the Hybrid Monte Carlo and Multipoint Hybrid Monte Carlo sampling techniques described in Liu (2001): "Monte Carlo Strategies in Computing
Estimating Effects and Correlations in Neuroimaging Data
Good list of presenters: Gelman, Shalizi, the "Voodoo statistics" guy.
How to design a mini-lecture on statistical inference? - Statistical Modeling, Causal Inference, and Social Science
Teaching advice from Gelman
http://www.stanford.edu/~montanar/BOOK/book.html
It should be an introduction to a rich and rapidly evolving research field at the interface between statistical physics, theretical computer science/discrete mathematics, and coding/information theory. It should be accessible to graduate students an researchers without specific training in any of these three fields.
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