Correlation and Causality
by David A. Kenny
Publisher: John Wiley & Sons Inc 1979
Number of pages: 353
This text is a general introduction to the topic of structural analysis. It is an introduction because it presumes no previous acquaintance with causal analysis. It is general because it covers all the standard, as well as a few nonstandard, statistical procedures. Since the topic is structural analysis, and not statistics, very little discussion is given to the actual mechanics of estimation.
Home page url
Download or read it online for free here:
by Cosma Rohilla Shalizi
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).
by Thomas G. Kurtz - University of Wisconsin
Covered topics: stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson measures, stochastic differential equations for general Markov processes.
by Christophe Garban, Jeffrey E. Steif - arXiv
The goal of this set of lectures is to combine two seemingly unrelated topics: (1) The study of Boolean functions, a field particularly active in computer science; (2) Some models in statistical physics, mostly percolation.
by G. D'Agostini - arXiv
Triggered by a recent interesting article on the too frequent incorrect use of probabilistic evidence in courts, the author introduces the basic concepts of probabilistic inference with a toy model, and discusses several important issues.