Differential Geometrical Theory of Statistics
by Frederic Barbaresco, Frank Nielsen (eds)
Publisher: MDPI AG 2017
Number of pages: 474
Contents: Geometric Thermodynamics of Jean-Marie Souriau; Koszul-Vinberg Model of Hessian Information Geometry; Divergence Geometry and Information Geometry; Density of Probability on manifold and metric space; Statistics on Paths and on Riemannian Manifolds; Entropy and Complexity in Linguistic.
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by Peter Young - arXiv
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.
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 Sidney Tyrrell - BookBoon
This textbook is for people who want to know how to use SPSS for analyzing data. The author has considerable experience of teaching many such people and assumes they know the basics of statistics but nothing about SPSS, or as it is now known, PASW.
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.